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The Euclidean structure of real matrices
Imports 0 library modules and 8 external
External: HB.structures, mathcomp.classical.all_ssreflect_compat, mathcomp.finite_group.fingroup, mathcomp.finite_group.perm, mathcomp.algebra.algebraic_hierarchy.ssralg, mathcomp.algebra.numeric_hierarchy.ssrnum, mathcomp.algebra.matrix, mathcomp.algebra.ring_tactic
Imported by 67
- GaussianAnalysis.gaussian.lebesgue_rV
- GaussianAnalysis.matrix.real_spectral
- GaussianAnalysis.matrix.whitening
- GaussianAnalysis.matrix.opnorm
- GaussianAnalysis.matrix.lambda_max
- GaussianAnalysis.matrix.psd_splitting
- GaussianAnalysis.matrix.spectral_gap
- GaussianAnalysis.matrix.nets
- GaussianAnalysis.matrix.random_opnorm
- GaussianAnalysis.matrix.covering
- GaussianAnalysis.matrix.von_neumann
- GaussianAnalysis.matrix.psd_part
- GaussianAnalysis.matrix.effective_rank
- GaussianAnalysis.matrix.nuclear
- GaussianAnalysis.matrix.condition_cone
- GaussianAnalysis.matrix.trace_projection
- GaussianAnalysis.matrix.tensor_packing
- GaussianAnalysis.probability.subgaussian_matrix
- GaussianAnalysis.probability.small_ball_method
- GaussianAnalysis.probability.hanson_wright
- GaussianAnalysis.probability.measurable_minimizer
- GaussianAnalysis.probability.finite_gap
- GaussianAnalysis.random_matrix.goe
- GaussianAnalysis.random_matrix.goe_edge
- GaussianAnalysis.random_matrix.goe_rotation
- GaussianAnalysis.random_matrix.wigner
- GaussianAnalysis.random_matrix.restricted_isometry
- GaussianAnalysis.random_matrix.matrix_series
- GaussianAnalysis.random_matrix.goe_entries
- GaussianAnalysis.comparison.chi_square
- GaussianAnalysis.comparison.gauss_linear
- GaussianAnalysis.comparison.gauss_shift
- GaussianAnalysis.comparison.gauss_smoothing
- GaussianAnalysis.comparison.gauss_concentration
- GaussianAnalysis.comparison.slepian
- GaussianAnalysis.comparison.gordon
- GaussianAnalysis.comparison.escape
- GaussianAnalysis.comparison.cgmt
- GaussianAnalysis.comparison.cone_escape
- GaussianAnalysis.comparison.sudakov
- GaussianAnalysis.comparison.gauss_law
- GaussianAnalysis.comparison.brascamp_lieb
- GaussianAnalysis.comparison.brascamp_lieb_lebesgue
- GaussianAnalysis.convex.self_concordant
- GaussianAnalysis.convex.least_squares
- GaussianAnalysis.convex.logdet_barrier
- GaussianAnalysis.convex.minimizers
- GaussianAnalysis.convex.feature_moments
- GaussianAnalysis.convex.gauss_feature
- GaussianAnalysis.convex.ls_insertion
- GaussianAnalysis.convex.barrier_removal
- GaussianAnalysis.convex.barrier_lindeberg
- GaussianAnalysis.convex.ridge_comparison
- GaussianAnalysis.convex.moreau
- GaussianAnalysis.convex.feature_mixture
- GaussianAnalysis.fourier.charfun_rV
- GaussianAnalysis.fourier.small_ball
- GaussianAnalysis.fourier.inversion
- GaussianApplications.PsdSplittingStatement
- GaussianApplications.PsdSplittingTheorem
- GaussianApplications.TensorPackingStatement
- GaussianApplications.TensorPackingTheorem
- GaussianApplications.SKGapDefinitions
- GaussianApplications.SKGap.Ising
- GaussianApplications.SKGap.Disorder
- GaussianApplications.SKGap.TwoSpin
- GaussianApplications.SKGap.Poincare
Required by 57 files of the paper proofs
- extension/Condition/Cover.v
- extension/Condition/GaussianCone.v
- extension/Condition/GaussianGap.v
- extension/Condition/GaussianWitness.v
- extension/Condition/Sat.v
- extension/Condition/Slices.v
- extension/Condition/Unsat.v
- extension/ConditionKappa/Cone.v
- extension/ConditionKappa/GaussianGap.v
- extension/ConditionKappa/GaussianLimit.v
- extension/ConditionKappa/GaussianWitness.v
- extension/ConditionKappa/Geometry.v
- extension/ConditionKappa/Sat.v
- extension/ConditionKappa/Unsat.v
- extension/Features/Mixture.v
- extension/Features/Regular.v
- extension/Gaussian/Cones.v
- extension/Gaussian/FittingError.v
- extension/Gaussian/GaussianModel.v
- extension/Gaussian/Limit.v
- extension/Gaussian/Representation.v
- extension/Gaussian/Subcritical.v
- extension/Mixture/Interpolation.v
- extension/Sat/ApproximateFit.v
- extension/Sat/Apriori.v
- extension/Sat/AprioriSparse.v
- extension/Sat/EffectiveRank.v
- extension/Sat/Interpolation.v
- extension/Sat/LightTail.v
- extension/Sat/LightTailBound.v
- extension/Sat/OneStage.v
- extension/Sat/SmallResidual.v
- extension/Sat/SparseLimit.v
- extension/Sat/SparseLower.v
- extension/Sat/Universality.v
- extension/Unsat/FourthMomentThree.v
- extension/Unsat/GoeBridge.v
- extension/Unsat/LeastSquares.v
- extension/Unsat/Regularized.v
- extension/Unsat/Ridge.v
- extension/Unsat/Universality.v
- theories/Feature/DiagonalTrace.v
- theories/Gaussian/Lipschitz/Concentration.v
- theories/Gaussian/Lipschitz/Variance.v
- theories/Gaussian/Orthogonal/WeightedSquareTail.v
- theories/Gaussian/Tail/UnitLinear.v
- theories/Gordon/EscapeExpectation.v
- theories/Gordon/Processes.v
- theories/Head/TailSupport.v
- theories/Spectral/Cutoff.v
- theories/Spectral/OperatorNet.v
- theories/Spectral/OperatorTransport.v
- theories/Spectral/OrthogonalBounds.v
- theories/Spectral/SymmetricDiagonalization.v
- theories/SquareFree/EdgeLower.v
- theories/SquareFree/EdgeUpper.v
- theories/SquareFree/WalkNBEvent.v
The Frobenius inner product and norm of rectangular matrices, and orthogonal matrices. On row and column vectors, the Frobenius inner product and norm are the Euclidean inner product and norm.
mxdot A B | the Frobenius inner product of A, B : 'M[R]_(m, n), \sum_i \sum_j A i j * B i j |
frobenius A | the Frobenius norm Num.sqrt (mxdot A A) of A; the Euclidean norm when A is a row or a column vector |
M \is orthogonalmx | the square matrix M is orthogonal: M *m M^T = 1 |
Main results
| Results | Statement | Used by theories/ |
|---|---|---|
mxdot A B, the sum of the A_(i, j) B_(i, j), is the Frobenius inner product of real matrices and frobenius A its norm. Cauchy-Schwarz holds, and the norm satisfies the triangle inequality and is submultiplicative. On row and column vectors they are the Euclidean inner product and norm. | Spectral/, Spectral/, Feature/, SquareFree/, SquareFree/, Gaussian/, Gaussian/, Gaussian/, Gaussian/, Gordon/, Gordon/; in the library, the nine files of comparison/ that handle vectors. mxdot_cauchy_schwarz and frobeniusD are used inside the library only | |
The orthogonal matrices (M M^T = 1). Multiplying by an orthogonal matrix, on either side, preserves the Frobenius inner product and norm. | Spectral/, Spectral/ |
Declarations64 exported
Variable R : comNzRingType. Implicit Types m n p : nat.
forall [R : comNzRingType] [m n : nat], 'M_(m, n) -> 'M_(m, n) -> RDefinition mxdot m n (A B : 'M[R]_(m, n)) : R := \sum_i \sum_j A i j * B i j.
mxdot A B, the sum of the A_(i, j) B_(i, j), is the Frobenius inner product of real matrices and frobenius A its norm. Cauchy-Schwarz holds, and the norm satisfies the triangle inequality and is submultiplicative. On row and column vectors they are the Euclidean inner product and norm.
theories/ by: Spectral/SymmetricDiagonalization , Spectral/OperatorNet , Feature/DiagonalTrace , SquareFree/EdgeLower , SquareFree/WalkNBEvent , Gaussian/Tail/UnitLinear , Gaussian/Lipschitz/Concentration , Gaussian/Lipschitz/Variance , Gaussian/Orthogonal/WeightedSquareTail , Gordon/EscapeExpectation , Gordon/Processes ; in the library, the nine files of comparison/ that handle vectors. mxdot_cauchy_schwarz and frobeniusD are used inside the library onlyUsed by 596 declarations in 60 files
- GaussianAnalysis.gaussian.lebesgue_rV: gauss_pdf, measurable_mxdotB, measurable_gauss_pdf, mxdot_rV_cons_self, gauss_pdf_cons, lebesgue_rV_gauss_integral, lebesgue_rV_ball_le, ge0_integral_gauss_pdf, ge0_integral_lebesgue_rV_gauss
- this file: mxdotC, mxdotDl, mxdotDr, mxdotZl, mxdotZr, mxdotNl, mxdotNr, mxdotBl, mxdotBr, mxdot0l, mxdot0r, mxdot_suml, mxdot_sumr, mxdot_trmx, mxdot_trace, mxdot_mulmxl, mxdot_mulmxr, mxdot_rowE, mxdot_colE, mxdot_outer, mxdot_outer2, mxdot_diag, mxdot_delta, mxdot_ge0, mxdot_eq0, mxdot_gt0, mxdot_cauchy_schwarz, sum_cauchy_schwarz, mxdot_entry, frobenius, frobenius_sqr, mxdot_le, ler_mxdot, frobeniusD, frobenius_mulmx, mxdot_orthogonalmxl, mxdot_orthogonalmxr
- GaussianAnalysis.matrix.real_spectral: continuous_mxdot, compact_unit_sphere, householder, householderK, householder_swap, mxdot_mulmx_sym, psd_form_eq0, rayleigh_max, symmetric_eigenvector, symmetric_spectral, orthogonalmx_row_unit, spectral_mxdot, spectral_form, spectral_form_le, spectral_form_ge, spectral_psd, spectral_form_abs
- GaussianAnalysis.matrix.whitening: sym_spectral_diag_ge, whitening_mxP, frobenius_whitening_mx, whitening_exists
- GaussianAnalysis.matrix.opnorm: mxdot_col, mxdot_opnorm, opnorm_bilinearP, opnorm_symP, opnorm_le_form_exp
- GaussianAnalysis.matrix.lambda_max: lambda_max, mxdot_unit_dim, lambda_max_set_neq0, lambda_max_ubound, lambda_max_has_sup, lambda_max_ub, lambda_max_le, lambda_max_form, lambda_max_attained, lambda_max_eigenvector, eigenvalue_le_lambda_max, opnorm_lambda_max
- GaussianAnalysis.matrix.psd_splitting: mxdot_block0, mxdot_sym_tr, two_matrix_split, mxdot_compress
- GaussianAnalysis.matrix.spectral_gap: mulmx_col_mxdot, psd_square_gap, mxdot_mulmx_sum, opnorm_row_sum
- GaussianAnalysis.matrix.nets: mxdot_net_bound, opnorm_net_sphere, opnorm_net_bilinear, form_unit_ball_le, opnorm_net_sym, frobenius_col_sqr
- GaussianAnalysis.matrix.random_opnorm: mxdot_trmx_form, sym_part_form, mxdot_sym_part, mxdot_psd_le, opnorm_sym_part_net, opnorm_sum_subexponential
- GaussianAnalysis.matrix.covering: mxdot_vec_mx, frob_sep, dual_ball_covering, product_covering, matrix_small_ball
- GaussianAnalysis.matrix.von_neumann: mxdot_spec, hoffman_wielandt
- GaussianAnalysis.matrix.psd_part: psdmx, mxdot_psd_ge0, psd_nearest, psd_partE, psd_part_moreau, psd_part_nonexpansive, mxdot_spec_le, mxdot_psd_part_shift
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.nuclear: nuclear, nuclear_has_sup, nuclear_ub, nuclear_le, mxdot_le_nuclear, nuclear_outer, nuclear_spectral, nuclear_sym, coef_map, mxdot_coef_map, mxdot_vec_mxr, range_duality, range_duality_sym
- GaussianAnalysis.matrix.condition_cone: cond_cone, cond_cone_convex, cond_cone_quad, mxdot_quad_vec, continuous_mxdotv, cond_cone_vec_closed, cond_clip_energy, cond_energy_le, cond_cone_dist, mxdot_vec_mx, cond_support, cond_support_vec, cond_support_sqr, cond_support_sym, cond_slice_t, cond_slice_form, cond_slice_frobenius, cond_slice_vec_closed, cond_slice_vec_frobenius
- GaussianAnalysis.matrix.trace_projection: mxdot1l, mxtrace_sqr_le, trace_pen_ge, mxdot_conjmx, trace_quad, mxdot_trace_scalel, trace_scale_adj, trace_quad_expand
- and 436 more
Used by 74 declarations in 34 files
- this file: mxdotDr, mxdotZr, mxdotNr, mxdot0r, mxdot_sumr, mxdot_outer, mxdot_outer2, mxdot_cauchy_schwarz, frobeniusD
- GaussianAnalysis.matrix.real_spectral: householder_swap, spectral_form
- GaussianAnalysis.matrix.whitening: sym_spectral_diag_ge
- GaussianAnalysis.matrix.opnorm: mxdot_delta_opnorm, opnorm_trmx
- GaussianAnalysis.matrix.psd_splitting: mxdot_block0
- GaussianAnalysis.matrix.random_opnorm: mxdot_trmx_form
- GaussianAnalysis.matrix.covering: frob_sep
- GaussianAnalysis.matrix.von_neumann: hoffman_wielandt
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_part_nonexpansive
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.nuclear: nuclear_outer, nuclear_spectral, range_duality
- GaussianAnalysis.matrix.condition_cone: mxdot_quad_vec, cond_cone_vec_closed, cond_slice_vec_closed
- GaussianAnalysis.matrix.trace_projection: mxtrace_sqr_le, trace_scale_adj, trace_quad_expand, mxtrace_vec_mx, trace_argmax_lipschitz
- GaussianAnalysis.matrix.tensor_packing: bessel_mxdot, frobenius_rowperp_le, gram_form, mxdot_tensor_form
- GaussianAnalysis.probability.subgaussian_matrix: subgaussian_opnorm_tail
- GaussianAnalysis.random_matrix.restricted_isometry: gram_offC, mxdot_sum_disj, tuple_submx_net
- GaussianAnalysis.comparison.gauss_shift: measurable_mxdotl, ge0_integral_gauss_shift
- GaussianAnalysis.comparison.gauss_smoothing: gauss_smooth_shift
- GaussianAnalysis.comparison.escape: minmax_bil_sph_le, mxdot_proj
- GaussianAnalysis.comparison.cgmt: escape_inf_minimax
- GaussianAnalysis.comparison.sudakov: sudakov_minoration
- GaussianAnalysis.comparison.brascamp_lieb: tight_frame_mxdot_sqr, tight_frame_cauchy_schwarz
- GaussianAnalysis.convex.logdet_barrier: posdefmx_congruence
- GaussianAnalysis.convex.minimizers: vspace_orthonormal, ls_ridge_expand, continuous_ls_reduced, quad_response
- GaussianAnalysis.convex.feature_moments: form_le_opnorm
- GaussianAnalysis.convex.gauss_feature: gauss_mxdot_moments
- GaussianAnalysis.convex.ls_insertion: ins_hformC, ins_ell_quadratic, ins_form_le, ins_T_frobenius
- GaussianAnalysis.convex.barrier_removal: mxdot_convex
- GaussianAnalysis.convex.barrier_lindeberg: loo_compare
- GaussianAnalysis.convex.moreau: proj_variational, moreau, moreau_norm, cone_proj_support
- GaussianAnalysis.fourier.charfun_rV: cf_rV_regularization
- GaussianAnalysis.fourier.small_ball: cf_rV_norm_frame, contraction_trmx, cf_rV_regularized_le, vector_small_ball, vector_small_ball_variance
- GaussianAnalysis.fourier.inversion: integral_cf_rV_kernel_gauss
- GaussianApplications.SKGap.Ising: mxdot_deltal
Statement as written in the source
Used by 29 declarations in 18 files
- this file: mxdotDr, mxdotBl, mxdot_suml, frobeniusD
- GaussianAnalysis.matrix.real_spectral: psd_form_eq0
- GaussianAnalysis.matrix.random_opnorm: mxdot_sym_part
- GaussianAnalysis.matrix.nuclear: nuclearD
- GaussianAnalysis.matrix.condition_cone: cond_support_sym
- GaussianAnalysis.matrix.trace_projection: mxdot_trace_scalel
- GaussianAnalysis.matrix.tensor_packing: frobenius_rowperp_le, mxcoefD
- GaussianAnalysis.random_matrix.goe_rotation: goe_equiv_pair
- GaussianAnalysis.random_matrix.restricted_isometry: gram_offDl, mxdot_sum_disj
- GaussianAnalysis.random_matrix.goe_entries: mxdot_goe_coef_row, frobenius_goe_coef_diag
- GaussianAnalysis.comparison.cgmt: escape_inf_minimax
- GaussianAnalysis.comparison.brascamp_lieb: is_derive_mxdot, continuous_mxdot_line
- GaussianAnalysis.convex.minimizers: ls_ridge_expand, continuous_ls_reduced, quad_response
- GaussianAnalysis.convex.ls_insertion: ins_hform_linearl
- GaussianAnalysis.convex.barrier_removal: mxdot_convex
- GaussianAnalysis.convex.moreau: polar_convex, moreau_norm, cone_proj_support
- GaussianAnalysis.fourier.charfun_rV: cf_rV_add
- GaussianApplications.SKGap.Ising: quad_expand
Statement as written in the source
Used by 36 declarations in 22 files
- this file: mxdotBr, frobeniusD
- GaussianAnalysis.matrix.real_spectral: psd_form_eq0
- GaussianAnalysis.matrix.lambda_max: lambda_maxD
- GaussianAnalysis.matrix.psd_splitting: psdmxD, two_matrix_split
- GaussianAnalysis.matrix.random_opnorm: sym_part_form
- GaussianAnalysis.matrix.nuclear: nuclear_sym, range_duality, range_duality_sym
- GaussianAnalysis.matrix.condition_cone: cond_cone_convex
- GaussianAnalysis.matrix.tensor_packing: frobenius_rowperp_le
- GaussianAnalysis.random_matrix.goe_edge: goe_mx_form
- GaussianAnalysis.random_matrix.goe_rotation: goe_equiv_pair
- GaussianAnalysis.random_matrix.restricted_isometry: mxdot_sum_disj
- GaussianAnalysis.random_matrix.goe_entries: goe_mx_mxdot, mxdot_goe_coef_row, frobenius_goe_coef_diag
- GaussianAnalysis.comparison.cgmt: escape_inf_minimax
- GaussianAnalysis.convex.logdet_barrier: posdefmx_convex, posdefmx_open
- GaussianAnalysis.convex.minimizers: ls_ridge_expand, ls_bopt_linear, continuous_ls_reduced, quad_response
- GaussianAnalysis.convex.gauss_feature: gauss_mxdot_moments
- GaussianAnalysis.convex.ls_insertion: ins_hform_linearl, ins_taylor, ins_ell_quadratic
- GaussianAnalysis.convex.barrier_removal: mxdot_convex, ls_objective_convex
- GaussianAnalysis.convex.barrier_lindeberg: loo_compare
- GaussianAnalysis.convex.moreau: moreau_norm
- GaussianAnalysis.fourier.inversion: integral_cf_rV_kernel_gauss
- GaussianApplications.SKGap.Ising: quad_expand, lin_expand
Statement as written in the source
Used by 56 declarations in 28 files
- this file: mxdotZr, mxdotNl, mxdot_cauchy_schwarz, frobeniusZ
- GaussianAnalysis.matrix.real_spectral: psd_form_eq0, rayleigh_max
- GaussianAnalysis.matrix.lambda_max: lambda_max_form
- GaussianAnalysis.matrix.spectral_gap: psd_square_gap
- GaussianAnalysis.matrix.nets: opnorm_net_sphere, form_unit_ball_le
- GaussianAnalysis.matrix.random_opnorm: mxdot_sym_part
- GaussianAnalysis.matrix.nuclear: nuclearZ, mxdot_coef_map
- GaussianAnalysis.matrix.condition_cone: cond_support_sym, cond_supportZ
- GaussianAnalysis.matrix.trace_projection: mxdot_trace_scalel
- GaussianAnalysis.matrix.tensor_packing: bessel_mxdot
- GaussianAnalysis.probability.small_ball_method: small_ball_linear
- GaussianAnalysis.probability.hanson_wright: hw_decoupled_mgf
- GaussianAnalysis.random_matrix.goe_rotation: goe_equiv_pair
- GaussianAnalysis.random_matrix.restricted_isometry: mxdot_tuple_mx, cross_tail, gram_offZl, gram_off_rip, tuple_mx_dot_tail
- GaussianAnalysis.random_matrix.goe_entries: mxdot_goe_coef_row, frobenius_goe_coef_diag, goe_mx_row_tail
- GaussianAnalysis.comparison.gauss_smoothing: gauss_smooth_shift
- GaussianAnalysis.comparison.cgmt: escape_inf_minimax
- GaussianAnalysis.comparison.sudakov: dual_sudakov
- GaussianAnalysis.comparison.brascamp_lieb: tight_frame_cauchy_schwarz, is_derive_mxdot, continuous_mxdot_line, key
- GaussianAnalysis.convex.minimizers: ls_ridge_expand, continuous_ls_reduced, quad_response
- GaussianAnalysis.convex.ls_insertion: ins_hform_linearl, ins_form_le, ins_v_bound
- GaussianAnalysis.convex.barrier_removal: mxdot_convex
- GaussianAnalysis.convex.moreau: proj_variational, polar_convex, cone_proj_support
- GaussianAnalysis.convex.feature_mixture: mixture_regular_feature_dot
- GaussianAnalysis.fourier.charfun_rV: cf_rV_tuple_prod, cf_rV_regularization, gauss_pdf_scale, cf_rV_regularization_le
- GaussianAnalysis.fourier.small_ball: cf_rV_regularized_le, vector_small_ball, vector_small_ball_variance
- GaussianAnalysis.fourier.inversion: cf_rV_density_regE, integral_cf_rV_kernel_gauss
- GaussianApplications.SKGap.Ising: quad_expand
Statement as written in the source
Used by 73 declarations in 34 files
- this file: mxdot_cauchy_schwarz, frobeniusZ
- GaussianAnalysis.matrix.real_spectral: psd_form_eq0, rayleigh_max, symmetric_eigenvector, spectral_form_le, spectral_form_ge
- GaussianAnalysis.matrix.opnorm: opnorm_spectral
- GaussianAnalysis.matrix.lambda_max: lambda_max_form, lambda_max_eigenvector, eigenvalue_le_lambda_max
- GaussianAnalysis.matrix.spectral_gap: psd_square_gap
- GaussianAnalysis.matrix.nets: form_unit_ball_le
- GaussianAnalysis.matrix.random_opnorm: sym_part_form, opnorm_sum_subexponential
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.nuclear: mxdot_le_nuclear, nuclear_sym, range_duality, range_duality_sym
- GaussianAnalysis.matrix.condition_cone: cond_coneZ, cond_cone_convex, cond_cone_quad, cond_cone_vec_closed, cond_supportZ
- GaussianAnalysis.matrix.tensor_packing: bessel_mxdot, sudakov_mx_series
- GaussianAnalysis.probability.hanson_wright: hw_decoupled_mgf
- GaussianAnalysis.random_matrix.goe_edge: goe_mx_form
- GaussianAnalysis.random_matrix.goe_rotation: goe_equiv_pair
- GaussianAnalysis.random_matrix.restricted_isometry: mxdot_tuple_mx, cross_tail, gram_off_rip
- GaussianAnalysis.random_matrix.goe_entries: goe_mx_mxdot, mxdot_goe_coef_row, frobenius_goe_coef_diag, goe_mx_row_tail
- GaussianAnalysis.comparison.gauss_smoothing: gauss_smooth_shift
- GaussianAnalysis.comparison.escape: rmax_net_ge, gwidth_range_sphere, gwidth_sphere
- GaussianAnalysis.comparison.cgmt: unit_dir, escape_inf_minimax
- GaussianAnalysis.comparison.cone_escape: cone_sup_dot, cgmt_aux_cone_zero
- GaussianAnalysis.comparison.sudakov: dual_sudakov
- GaussianAnalysis.comparison.brascamp_lieb: key
- GaussianAnalysis.convex.self_concordant: sc_barrier_contraction
- GaussianAnalysis.convex.logdet_barrier: posdefmx_spectral, posdefmx_convex, posdefmx_scalar
- GaussianAnalysis.convex.minimizers: ls_ridge_expand, ls_bopt_linear, continuous_ls_reduced, quad_response
- GaussianAnalysis.convex.gauss_feature: gauss_mxdot_moments
- GaussianAnalysis.convex.ls_insertion: ins_hform_linearl, ins_form_le, ins_v_bound
- GaussianAnalysis.convex.barrier_removal: mxdot_convex, ls_objective_convex
- GaussianAnalysis.convex.barrier_lindeberg: loo_compare
- GaussianAnalysis.convex.moreau: proj_variational, cone_proj_support
- GaussianAnalysis.fourier.charfun_rV: cf_rV_regularization, gauss_pdf_scale, cf_rV_regularization_le
- GaussianAnalysis.fourier.small_ball: frame_mxdot, cf_rV_regularized_le
- GaussianAnalysis.fourier.inversion: cf_rV_density_regE, integral_cf_rV_kernel_gauss
- GaussianApplications.SKGap.Ising: quad_expand, lin_expand
Statement as written in the source
Used by 18 declarations in 12 files
- this file: mxdotNr, mxdotBl
- GaussianAnalysis.matrix.real_spectral: householderN
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_partE, psd_part_nonexpansive
- GaussianAnalysis.probability.hanson_wright: hanson_wright
- GaussianAnalysis.comparison.chi_square: gauss_centered_chi2_lower_tail
- GaussianAnalysis.comparison.gauss_concentration: gauss_concentration_smooth
- GaussianAnalysis.comparison.escape: gwidth_norm, gauss_opnorm_mean
- GaussianAnalysis.comparison.cgmt: escape_inf_minimax, low_aux
- GaussianAnalysis.comparison.sudakov: gauss_shift_sym
- GaussianAnalysis.convex.ls_insertion: ins_alphaE, ins_ell_quadratic
- GaussianAnalysis.convex.barrier_removal: mxdot_convex
- GaussianAnalysis.fourier.inversion: integral_gauss_pdf_inv_prob
Statement as written in the source
Used by 16 declarations in 15 files
- this file: mxdotBr
- GaussianAnalysis.matrix.real_spectral: householderN
- GaussianAnalysis.matrix.lambda_max: opnorm_lambda_max
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_partE
- GaussianAnalysis.matrix.nuclear: mxdot_le_nuclear
- GaussianAnalysis.matrix.condition_cone: cond_cone_vec_closed
- GaussianAnalysis.matrix.trace_projection: trace_argmax_cone
- GaussianAnalysis.probability.hanson_wright: hanson_wright
- GaussianAnalysis.comparison.chi_square: gauss_centered_chi2_lower_tail
- GaussianAnalysis.comparison.gauss_concentration: gauss_concentration_smooth
- GaussianAnalysis.comparison.sudakov: gauss_shift_sym
- GaussianAnalysis.convex.ls_insertion: ins_ell_quadratic
- GaussianAnalysis.convex.barrier_removal: mxdot_convex
- GaussianAnalysis.convex.moreau: cone_projP
- GaussianAnalysis.fourier.inversion: integral_gauss_pdf_inv_prob
Statement as written in the source
Used by 29 declarations in 19 files
- this file: mxdot_cauchy_schwarz
- GaussianAnalysis.matrix.real_spectral: householder_swap
- GaussianAnalysis.matrix.psd_splitting: two_matrix_split
- GaussianAnalysis.matrix.nets: mxdot_net_bound
- GaussianAnalysis.matrix.von_neumann: hoffman_wielandt
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_part_nonexpansive
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.trace_projection: trace_quad_expand, trace_argmax_lipschitz, trace_argmax_cone
- GaussianAnalysis.matrix.tensor_packing: bessel_mxdot, mxcoefB
- GaussianAnalysis.probability.small_ball_method: mxdot_form_lipschitz, small_ball_linear
- GaussianAnalysis.random_matrix.goe_edge: lambda_max_net_le
- GaussianAnalysis.comparison.escape: gwidth_lipschitz
- GaussianAnalysis.comparison.cgmt: cgmt_aux_lipschitz, Xp_y, Yp_z
- GaussianAnalysis.comparison.cone_escape: cone_sup_lipschitz
- GaussianAnalysis.comparison.sudakov: sudakov_minoration
- GaussianAnalysis.convex.minimizers: quad_response
- GaussianAnalysis.convex.ls_insertion: ins_form_le
- GaussianAnalysis.convex.moreau: proj_variational, proj_unique, proj_nonexpansive, polar_convex
- GaussianAnalysis.convex.feature_mixture: mixture_regular_feature_dot
Statement as written in the source
Used by 35 declarations in 22 files
- this file: mxdot_cauchy_schwarz
- GaussianAnalysis.matrix.real_spectral: householder_swap, symmetric_eigenvector
- GaussianAnalysis.matrix.lambda_max: lambda_max_eigenvector
- GaussianAnalysis.matrix.psd_splitting: two_matrix_split
- GaussianAnalysis.matrix.nets: mxdot_net_bound
- GaussianAnalysis.matrix.von_neumann: hoffman_wielandt
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_part_nonexpansive
- GaussianAnalysis.matrix.nuclear: range_duality
- GaussianAnalysis.matrix.condition_cone: cond_cone_convex, cond_cone_vec_closed
- GaussianAnalysis.matrix.trace_projection: trace_quad_expand, trace_argmax_lipschitz
- GaussianAnalysis.matrix.tensor_packing: bessel_mxdot
- GaussianAnalysis.probability.small_ball_method: mxdot_form_lipschitz
- GaussianAnalysis.random_matrix.goe_edge: lambda_max_net_le
- GaussianAnalysis.comparison.escape: rmax_net_ge, rmax_net_width
- GaussianAnalysis.comparison.cgmt: escape_inf_minimax, Xp_x, Xp_w, Yp_x, Yp_y
- GaussianAnalysis.comparison.cone_escape: cone_sup_attained
- GaussianAnalysis.comparison.sudakov: sudakov_minoration
- GaussianAnalysis.convex.logdet_barrier: posdefmx_convex
- GaussianAnalysis.convex.minimizers: quad_response
- GaussianAnalysis.convex.ls_insertion: ins_form_le
- GaussianAnalysis.convex.moreau: proj_variational, proj_unique, proj_nonexpansive, cone_projP, moreau
- GaussianAnalysis.fourier.charfun_rV: cf_rV_regularization
forall [R : comNzRingType] [m n : nat] (A : 'M_(m, n)), mxdot 0 A = 0
Statement as written in the source
Lemma mxdot0l m n (A : 'M[R]_(m, n)) : mxdot 0 A = 0.
Used by 38 declarations in 22 files
- this file: mxdot0r, mxdot_suml, mxdot_eq0, mxdot_cauchy_schwarz, frobenius0
- GaussianAnalysis.matrix.real_spectral: rayleigh_max
- GaussianAnalysis.matrix.lambda_max: lambda_max_form
- GaussianAnalysis.matrix.nets: form_unit_ball_le
- GaussianAnalysis.matrix.nuclear: nuclear_eq0
- GaussianAnalysis.matrix.condition_cone: cond_supportZ
- GaussianAnalysis.matrix.trace_projection: trace_argmax0
- GaussianAnalysis.probability.hanson_wright: hanson_wright_upper
- GaussianAnalysis.random_matrix.goe_rotation: goe_diag_var_tail
- GaussianAnalysis.random_matrix.restricted_isometry: cross_tail, has_sup_rip, rip_const_ge0, gram_off_rip, mxdot_sum_disj
- GaussianAnalysis.random_matrix.matrix_series: opnorm_le_sym_dilation
- GaussianAnalysis.random_matrix.goe_entries: goe_mx_row_tail
- GaussianAnalysis.comparison.gauss_shift: ge0_integral_gauss_shift
- GaussianAnalysis.comparison.escape: rmax_net_ge, gwidth_range_sphere, gwidth_sphere
- GaussianAnalysis.comparison.cgmt: unit_dir, escape_inf_minimax
- GaussianAnalysis.comparison.brascamp_lieb: gauss_ibp_unit, Lambda_lip
- GaussianAnalysis.convex.logdet_barrier: posdefmx_spectral
- GaussianAnalysis.convex.minimizers: quad_response
- GaussianAnalysis.convex.ls_insertion: ins_hessian_pd, ins_c0_bounds, ins_T_bounds, ins_v_bound
- GaussianAnalysis.convex.moreau: polar0, cone_proj_support
- GaussianAnalysis.fourier.charfun_rV: cf_rV_gauss
- GaussianAnalysis.fourier.small_ball: cf_rV_regularized_le
forall [R : comNzRingType] [m n : nat] (A : 'M_(m, n)), mxdot A 0 = 0
Statement as written in the source
Lemma mxdot0r m n (A : 'M[R]_(m, n)) : mxdot A 0 = 0.
Used by 18 declarations in 14 files
- this file: mxdot_cauchy_schwarz
- GaussianAnalysis.matrix.real_spectral: rayleigh_max
- GaussianAnalysis.matrix.psd_splitting: psdmx0
- GaussianAnalysis.matrix.nuclear: nuclear_ge0, range_duality
- GaussianAnalysis.matrix.condition_cone: cond_cone0
- GaussianAnalysis.matrix.tensor_packing: mxdot_rowproj_perp
- GaussianAnalysis.random_matrix.restricted_isometry: cross_tail
- GaussianAnalysis.random_matrix.goe_entries: goe_mx_row_tail
- GaussianAnalysis.comparison.gauss_linear: gauss_mxdot, integral_gauss_expR_mxdot
- GaussianAnalysis.comparison.cgmt: low_aux
- GaussianAnalysis.comparison.cone_escape: cone_sup_ge0, cone_sup_dot, cgmt_aux_cone_zero
- GaussianAnalysis.convex.minimizers: ls_ridge_bopt
- GaussianAnalysis.convex.ls_insertion: ins_c0_bounds
- GaussianAnalysis.fourier.charfun_rV: cf_rV_gauss
forall [R : comNzRingType] [m n : nat] [I : Type] (r : seq I) (P : pred I) (F : I -> 'M_(m, n)) (B : 'M_(m, n)), mxdot (\sum_(k <- r | P k) F k) B = \sum_(k <- r | P k) mxdot (F k) B
Statement as written in the source
Used by 17 declarations in 10 files
- this file: mxdot_sumr
- GaussianAnalysis.matrix.psd_splitting: frobenius_sum_psd_le, psd_splitting_rel
- GaussianAnalysis.matrix.nuclear: mxdot_coef_map
- GaussianAnalysis.matrix.tensor_packing: almost_orthogonal_sum_le, bessel_mxdot, mxcoef_sum
- GaussianAnalysis.probability.small_ball_method: small_ball_linear
- GaussianAnalysis.random_matrix.restricted_isometry: mxdot_tuple_mx, cross_tail, tuple_mx_dot_tail
- GaussianAnalysis.comparison.brascamp_lieb: tight_frame_cauchy_schwarz, key
- GaussianAnalysis.convex.feature_mixture: mixture_regular_feature_dot
- GaussianAnalysis.fourier.charfun_rV: cf_rV_tuple_prod
- GaussianAnalysis.fourier.small_ball: vector_small_ball, vector_small_ball_variance
forall [R : comNzRingType] [m n : nat] [I : Type] (r : seq I) (P : pred I) (F : I -> 'M_(m, n)) (A : 'M_(m, n)), mxdot A (\sum_(k <- r | P k) F k) = \sum_(k <- r | P k) mxdot A (F k)
Statement as written in the source
Used by 13 declarations in 7 files
- GaussianAnalysis.matrix.psd_splitting: frobenius_compress_le, frobenius_sum_psd_le, psd_splitting_rel
- GaussianAnalysis.matrix.random_opnorm: opnorm_sum_subexponential
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.tensor_packing: almost_orthogonal_sum_le, bessel_mxdot, gram_form, sudakov_mx_series
- GaussianAnalysis.random_matrix.restricted_isometry: mxdot_tuple_mx, mxdot_sum_disj
- GaussianAnalysis.comparison.brascamp_lieb: key
- GaussianAnalysis.fourier.small_ball: frame_mxdot
Statement as written in the source
Used by 26 declarations in 19 files
- this file: mxdot_colE, frobenius_trmx
- GaussianAnalysis.matrix.real_spectral: rayleigh_max, orthogonalmx_row_unit
- GaussianAnalysis.matrix.whitening: sym_spectral_diag_ge
- GaussianAnalysis.matrix.random_opnorm: mxdot_sym_part
- GaussianAnalysis.matrix.nuclear: nuclear_sym, range_duality_sym
- GaussianAnalysis.matrix.condition_cone: cond_support_sym
- GaussianAnalysis.matrix.tensor_packing: mxdot_tensor, tensor_packing
- GaussianAnalysis.probability.small_ball_method: mxdot_form_outer
- GaussianAnalysis.random_matrix.goe_edge: goe_mx_form
- GaussianAnalysis.random_matrix.goe_rotation: goe_equiv_form
- GaussianAnalysis.random_matrix.restricted_isometry: tuple_submx_net, sparse_norm_subgaussian
- GaussianAnalysis.comparison.cgmt: cgmt_aux_tr_set
- GaussianAnalysis.comparison.cone_escape: cone_sup_attained, cone_sup_tr_setE
- GaussianAnalysis.comparison.brascamp_lieb: gauss_ibp_unit
- GaussianAnalysis.convex.logdet_barrier: posdefmx_spectral, posdefmx_ge
- GaussianAnalysis.convex.feature_moments: form_le_opnorm
- GaussianAnalysis.convex.gauss_feature: gauss_mxdot_moments
- GaussianAnalysis.convex.ls_insertion: ins_T_frobenius
- GaussianAnalysis.convex.feature_mixture: mixture_regular_feature_dot
forall [R : comNzRingType] [m n : nat] (A B : 'M_(m, n)), mxdot A B = \tr (A *m B^T)
Statement as written in the source
Lemma mxdot_trace m n (A B : 'M[R]_(m, n)) : mxdot A B = \tr (A *m B^T).
Used by 29 declarations in 19 files
- this file: mxdot_mulmxl, mxdot_mulmxr, mxdot_rowE
- GaussianAnalysis.matrix.real_spectral: mxtrace_ABAB_le
- GaussianAnalysis.matrix.psd_splitting: mxtrace_psd_ge0, frobenius_sqr_sym, mxdot_block0, mxdot_sym_tr
- GaussianAnalysis.matrix.random_opnorm: mxdot_psd_le
- GaussianAnalysis.matrix.von_neumann: hoffman_wielandt
- GaussianAnalysis.matrix.psd_part: mxdot_psd_ge0, mxdot_spec_le
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.nuclear: frobenius_le_opnorm, nuclear_spectral
- GaussianAnalysis.matrix.condition_cone: cond_slice_vec_closed
- GaussianAnalysis.matrix.trace_projection: mxdot1l
- GaussianAnalysis.matrix.tensor_packing: gram_trace
- GaussianAnalysis.probability.hanson_wright: gauss_chaos_mgf
- GaussianAnalysis.random_matrix.goe_rotation: mxdot_conj
- GaussianAnalysis.random_matrix.matrix_series: gauss_mx_series_opnorm_moment, gauss_mx_series_opnorm_log
- GaussianAnalysis.comparison.escape: gauss_sqr_mulmx, gauss_proj_mean_ge
- GaussianAnalysis.comparison.cgmt: frobenius_hsub_sqr
- GaussianAnalysis.comparison.brascamp_lieb: tight_frame_mxdot, tight_frame_sum
- GaussianAnalysis.convex.ls_insertion: mxdot_row_mx
- GaussianAnalysis.fourier.small_ball: frame_trace
forall [R : comNzRingType] [m n p : nat] (A : 'M_(m, n)) (B : 'M_(n, p)) (C : 'M_(m, p)), mxdot (A *m B) C = mxdot B (A^T *m C)
Statement as written in the source
Used by 20 declarations in 10 files
- this file: mxdot_outer, mxdot_orthogonalmxl
- GaussianAnalysis.matrix.real_spectral: mxdot_mulmx_sym, spectral_form
- GaussianAnalysis.matrix.opnorm: opnorm_trmx
- GaussianAnalysis.matrix.psd_splitting: psdmx_conj, two_matrix_split, mxdot_compress
- GaussianAnalysis.matrix.random_opnorm: mxdot_trmx_form
- GaussianAnalysis.matrix.tensor_packing: frobenius_trmx_isometry, frobenius_isometry_le, mxdot_rowproj_perp, frobenius_rowproj, gram_form, tensor_packing
- GaussianAnalysis.probability.small_ball_method: mxdot_form_outer
- GaussianAnalysis.probability.hanson_wright: gauss_chaos_mgf
- GaussianAnalysis.comparison.escape: mxdot_proj, frobenius_proj_le
- GaussianAnalysis.convex.gauss_feature: opnorm_sqr_le
forall [R : comNzRingType] [m n p : nat] (A : 'M_(m, n)) (B : 'M_(n, p)) (C : 'M_(m, p)), mxdot (A *m B) C = mxdot A (C *m B^T)
Statement as written in the source
Used by 17 declarations in 10 files
- this file: mxdot_orthogonalmxr
- GaussianAnalysis.matrix.psd_splitting: two_matrix_split, mxdot_compress
- GaussianAnalysis.matrix.tensor_packing: tensor_packing
- GaussianAnalysis.comparison.escape: gauss_sqr_mulmx
- GaussianAnalysis.convex.logdet_barrier: posdefmx_congruence
- GaussianAnalysis.convex.minimizers: vspace_orthonormal, quad_response
- GaussianAnalysis.convex.gauss_feature: gauss_quad_moments, gauss_regular_feature
- GaussianAnalysis.convex.ls_insertion: ins_alphaE, ins_hformC, ins_norm_h, ins_ell_quadratic, ins_T_bounds
- GaussianAnalysis.convex.barrier_lindeberg: loo_compare
- GaussianAnalysis.fourier.small_ball: contraction_trmx
forall [R : comNzRingType] [n : nat] (u v : 'rV_n), mxdot u v = (u *m v^T) 0 0
Statement as written in the source
Lemma mxdot_rowE n (u v : 'rV[R]_n) : mxdot u v = (u *m v^T) 0 0.
Used by 15 declarations in 13 files
- this file: mxdot_colE, mxdot_outer, frobenius_rowE
- GaussianAnalysis.matrix.real_spectral: continuous_mxdot
- GaussianAnalysis.matrix.nuclear: range_duality
- GaussianAnalysis.matrix.condition_cone: continuous_mxdotv
- GaussianAnalysis.matrix.trace_projection: Vvec
- GaussianAnalysis.random_matrix.goe_rotation: goe_equiv_pair
- GaussianAnalysis.comparison.brascamp_lieb: mxdot_tr_mul
- GaussianAnalysis.convex.minimizers: continuous_ls_reduced
- GaussianAnalysis.convex.feature_moments: continuous_mxdotl
- GaussianAnalysis.convex.gauss_feature: gauss_mxdot_moments
- GaussianAnalysis.convex.ls_insertion: ins_ell_quadratic
- GaussianAnalysis.convex.moreau: continuous_dist2
- GaussianAnalysis.fourier.small_ball: mulmx_outer_rV
forall [R : comNzRingType] [n : nat] (x y : 'cV_n), mxdot x y = (x^T *m y) 0 0
Statement as written in the source
Lemma mxdot_colE n (x y : 'cV[R]_n) : mxdot x y = (x^T *m y) 0 0.
Used by 13 declarations in 8 files
- this file: mxdot_outer2, frobenius_colE
- GaussianAnalysis.matrix.real_spectral: householderK, householder_swap, rayleigh_max, symmetric_spectral
- GaussianAnalysis.matrix.psd_part: mxdot_psd_ge0
- GaussianAnalysis.matrix.nuclear: nuclear_outer, range_duality
- GaussianAnalysis.matrix.condition_cone: mxdot_quad_vec
- GaussianAnalysis.matrix.tensor_packing: sudakov_mx_series
- GaussianAnalysis.probability.subgaussian_matrix: subgaussian_opnorm_tail
- GaussianAnalysis.random_matrix.goe_edge: goe_mx_form
forall [R : comNzRingType] [m n : nat] (A : 'M_(m, n)) (x : 'cV_m) (y : 'cV_n), mxdot A (x *m y^T) = (x^T *m A *m y) 0 0
Statement as written in the source
Lemma mxdot_outer m n (A : 'M[R]_(m, n)) (x : 'cV[R]_m) (y : 'cV[R]_n) : mxdot A (x *m y^T) = (x^T *m A *m y) 0 0.
Used by 7 declarations in 6 files
- this file: mxdot_outer2
- GaussianAnalysis.matrix.nuclear: nuclear_outer, range_duality
- GaussianAnalysis.matrix.condition_cone: mxdot_quad_vec
- GaussianAnalysis.matrix.tensor_packing: mxdot_tensor_form
- GaussianAnalysis.probability.subgaussian_matrix: subgaussian_opnorm_tail
- GaussianAnalysis.random_matrix.goe_edge: goe_mx_form
forall [R : comNzRingType] [m n : nat] (a c : 'cV_m) (b e : 'cV_n), mxdot (a *m b^T) (c *m e^T) = mxdot a c * mxdot b e
Statement as written in the source
Used by 5 declarations in 5 files
- GaussianAnalysis.matrix.tensor_packing: mxdot_tensor
- GaussianAnalysis.probability.subgaussian_matrix: subgaussian_opnorm_tail
- GaussianAnalysis.probability.small_ball_method: mxdot_form_outer
- GaussianAnalysis.random_matrix.goe_edge: goe_form_cov
- GaussianAnalysis.convex.gauss_feature: gauss_mxdot_moments
forall [R : comNzRingType] [n : nat] (a b : 'rV_n), mxdot (diag_mx a) (diag_mx b) = \sum_i a 0 i * b 0 i
Statement as written in the source
Lemma mxdot_diag n (a b : 'rV[R]_n) : mxdot (diag_mx a) (diag_mx b) = \sum_i a 0 i * b 0 i.
Used by 6 declarations in 4 files
- GaussianAnalysis.matrix.real_spectral: spectral_mxdot
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_part_moreau, mxdot_psd_part_shift
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.convex.gauss_feature: gauss_quad_moments
forall [R : comNzRingType] [m n : nat] (A : 'M_(m, n)) (i : 'I_m) (j : 'I_n), mxdot A (delta_mx i j) = A i j
Statement as written in the source
Lemma mxdot_delta m n (A : 'M[R]_(m, n)) i j : mxdot A (delta_mx i j) = A i j.
Used by 31 declarations in 17 files
- GaussianAnalysis.matrix.real_spectral: rayleigh_max
- GaussianAnalysis.matrix.opnorm: mxdot_delta_opnorm, mx_norm_le_opnorm
- GaussianAnalysis.matrix.lambda_max: lambda_max_set_neq0, opnorm_lambda_max
- GaussianAnalysis.matrix.random_opnorm: mxdot_psd_le
- GaussianAnalysis.matrix.covering: colmax_le_opnorm
- GaussianAnalysis.matrix.nuclear: nuclear_spectral
- GaussianAnalysis.matrix.condition_cone: cond_cone_vec_closed
- GaussianAnalysis.probability.hanson_wright: entry_le_opnorm
- GaussianAnalysis.random_matrix.goe_rotation: conj_mx_orthogonal, goe_equiv_form, goe_equiv_diag, goe_equiv_pair
- GaussianAnalysis.random_matrix.matrix_series: mxtrace_mul_psd_le
- GaussianAnalysis.random_matrix.goe_entries: goe_mx_mxdot, mxdot_goe_coef_row, frobenius_goe_coef_diag
- GaussianAnalysis.comparison.gauss_smoothing: gauss_smooth_shift
- GaussianAnalysis.comparison.escape: gordon_escape, sym_sphere_net, gwidth_sphere, gauss_min_singular_mean, gauss_proj_singular_tail
- GaussianAnalysis.comparison.cgmt: unit_dir
- GaussianAnalysis.comparison.brascamp_lieb: gauss_ibp_unit
- GaussianAnalysis.convex.feature_moments: mxdot_quadE, mxdot_sqr_sum
- GaussianApplications.SKGap.Ising: mxdot_deltal, quad_expand, lin_expand
Variable R : realDomainType. Implicit Types m n : nat.
forall [R : realDomainType] [m n : nat] (A : 'M_(m, n)), 0 <= mxdot A A
Statement as written in the source
Lemma mxdot_ge0 m n (A : 'M[R]_(m, n)) : 0 <= mxdot A A.
Used by 80 declarations in 30 files
- this file: mxdot_gt0, mxdot_cauchy_schwarz, frobenius_sqr, frobenius_eq0
- GaussianAnalysis.matrix.real_spectral: mxtrace_ABAB_le
- GaussianAnalysis.matrix.whitening: frobenius_whitening_mx
- GaussianAnalysis.matrix.opnorm: opnorm_symP
- GaussianAnalysis.matrix.lambda_max: opnorm_lambda_max
- GaussianAnalysis.matrix.psd_splitting: two_matrix_split
- GaussianAnalysis.matrix.psd_part: psd_partE, psd_part_nearest
- GaussianAnalysis.matrix.nuclear: range_duality
- GaussianAnalysis.matrix.condition_cone: cond_cone1, cond_cone_convex, cond_cone_quad, cond_cone_dist
- GaussianAnalysis.matrix.trace_projection: mxtrace_sqr_le, trace_pen_ge, trace_argmax_unique
- GaussianAnalysis.matrix.tensor_packing: bessel_mxdot, frobenius_rowperp_le, gram_form_ge0, frobenius_tensor, opnorm_compress_gram
- GaussianAnalysis.probability.hanson_wright: gauss_chaos_mgf, hanson_wright_mgf
- GaussianAnalysis.probability.measurable_minimizer: ls_min_unique
- GaussianAnalysis.random_matrix.restricted_isometry: diag_part_le, gram_off_rip, gram_off_ball
- GaussianAnalysis.random_matrix.matrix_series: gauss_mx_series_opnorm_moment, gauss_mx_series_opnorm_log
- GaussianAnalysis.random_matrix.goe_entries: goe_mx_row_tail
- GaussianAnalysis.comparison.gauss_linear: gauss_mxdot
- GaussianAnalysis.comparison.brascamp_lieb: tight_frame_cauchy_schwarz
- GaussianAnalysis.convex.least_squares: ls_objective_ge0, ls_barrier_value_mono
- GaussianAnalysis.convex.minimizers: sc_minimizer, ls_ridge_ge0
- GaussianAnalysis.convex.feature_moments: reg_int_sqr, reg_int_lin, reg_int_lin2, reg_int_quad, quad_sqr_le, reg_int_resid2, reg_int_ell2, reg_int_resid4, reg_resid4
- GaussianAnalysis.convex.gauss_feature: gauss_integrable4, gauss_diag_moments, gauss_quad_moments, gauss_mxdot_moments, gauss_regular_feature
- GaussianAnalysis.convex.ls_insertion: ins_form_le
- GaussianAnalysis.convex.barrier_removal: mxdot_convex
- GaussianAnalysis.convex.barrier_lindeberg: ls_ridge_ge0', insertion_compare, loo_compare, objective_ge0, ref_point, barrier_lindeberg_mean, loo_variance, ref_moment_bound
- GaussianAnalysis.convex.moreau: proj_exists, proj_variational, proj_unique
- GaussianAnalysis.convex.feature_mixture: moment4_int_lin, moment4_int_lin2, moment4_int_quad, mixture_regular_feature_dot
- GaussianAnalysis.fourier.charfun_rV: prod_gauss_le_cf_rV, gauss_frobenius_ge, ball_le_cf_rV
- GaussianAnalysis.fourier.inversion: cvg_cf_rV_density_reg, reg_le, cf_rV_density_regE, integral_cf_rV_density, pdf_le2, lipschitz_add_gauss
- GaussianApplications.SKGap.Poincare: pair_quad_le
forall [R : realDomainType] [m n : nat] (A : 'M_(m, n)), (mxdot A A == 0) = (A == 0)
Statement as written in the source
Lemma mxdot_eq0 m n (A : 'M[R]_(m, n)) : (mxdot A A == 0) = (A == 0).
Used by 10 declarations in 7 files
- this file: mxdot_gt0, frobenius_eq0
- GaussianAnalysis.matrix.real_spectral: householderK, householder_swap, psd_form_eq0
- GaussianAnalysis.matrix.psd_part: psd_partE
- GaussianAnalysis.matrix.nuclear: range_duality
- GaussianAnalysis.matrix.trace_projection: trace_argmax_unique
- GaussianAnalysis.probability.measurable_minimizer: ls_min_unique
- GaussianAnalysis.convex.moreau: proj_unique
forall [R : realDomainType] [m n : nat] (A : 'M_(m, n)), (0 < mxdot A A) = (A != 0)
Statement as written in the source
Lemma mxdot_gt0 m n (A : 'M[R]_(m, n)) : (0 < mxdot A A) = (A != 0).
Used by 10 declarations in 8 files
- this file: mxdot_cauchy_schwarz, frobenius_gt0
- GaussianAnalysis.matrix.nets: form_unit_ball_le
- GaussianAnalysis.probability.hanson_wright: hanson_wright_upper
- GaussianAnalysis.random_matrix.restricted_isometry: cross_tail
- GaussianAnalysis.comparison.chi_square: gauss_centered_chi2_upper_tail
- GaussianAnalysis.convex.logdet_barrier: posdefmx_open, posdefmx_scalar
- GaussianAnalysis.convex.minimizers: vspace_orthonormal
- GaussianAnalysis.convex.ls_insertion: ins_hessian_pd
Stated in the README together with mxdot.
Statement as written in the source
Used by 14 declarations in 5 files
- this file: sum_cauchy_schwarz, mxdot_le
- GaussianAnalysis.matrix.trace_projection: mxtrace_sqr_le
- GaussianAnalysis.convex.feature_moments: reg_int_sqr, reg_int_lin, reg_int_lin2, reg_int_resid2, reg_int_ell2, reg_int_resid4
- GaussianAnalysis.convex.gauss_feature: gauss_quad_moments, gauss_regular_feature
- GaussianAnalysis.convex.feature_mixture: moment4_int_lin, moment4_int_lin2, mixture_regular_feature
forall [R : realDomainType] [n : nat] (a b : 'I_n -> R),
(\sum_i a i * b i) ^+ 2 <= (\sum_i a i * a i) * \sum_i b i * b iStatement as written in the source
Lemma sum_cauchy_schwarz n (a b : 'I_n -> R) : (\sum_i a i * b i) ^+ 2 <= (\sum_i a i * a i) * (\sum_i b i * b i).
Used by 9 declarations in 8 files
- this file: frobenius_mulmx
- GaussianAnalysis.matrix.nets: sum_abs_col_le
- GaussianAnalysis.matrix.von_neumann: spec_stat_lipschitz
- GaussianAnalysis.matrix.condition_cone: cond_slice_frobenius
- GaussianAnalysis.comparison.brascamp_lieb: tight_frame_cauchy_schwarz
- GaussianAnalysis.convex.logdet_barrier: logsum_sc, logsum_bp
- GaussianAnalysis.convex.feature_moments: mxdot_sqr_sum
- GaussianAnalysis.convex.barrier_lindeberg: sum_pred_sqr_le
forall [R : realDomainType] [m n : nat] (A : 'M_(m, n)) (i : 'I_m) (j : 'I_n), A i j ^+ 2 <= mxdot A A
Statement as written in the source
Lemma mxdot_entry m n (A : 'M[R]_(m, n)) i j : A i j ^+ 2 <= mxdot A A.
Used by 10 declarations in 7 files
- this file: frobenius_entry
- GaussianAnalysis.probability.measurable_minimizer: measurable_minimizer
- GaussianAnalysis.random_matrix.goe_rotation: goe_diag_var_tail
- GaussianAnalysis.random_matrix.restricted_isometry: has_sup_rip, level_cover
- GaussianAnalysis.comparison.gauss_concentration: herbst_DFL
- GaussianAnalysis.convex.gauss_feature: gauss_diag_moments, gauss_quad_moments, gauss_mxdot_moments
- GaussianAnalysis.convex.barrier_lindeberg: orthonormal_entry_le1
Variable R : rcfType. Implicit Types m n p : nat.
forall [R : rcfType] [m n : nat], 'M_(m, n) -> RDefinition frobenius m n (A : 'M[R]_(m, n)) : R := Num.sqrt (mxdot A A).
Stated in the README together with mxdot.
Used by 369 declarations in 49 files
- GaussianAnalysis.gaussian.lebesgue_rV: lebesgue_rV_ball_le
- this file: frobenius_ge0, frobenius_sqr, frobenius_eq0, frobenius_gt0, frobenius0, frobeniusZ, frobeniusN, frobenius_trmx, frobenius_rowE, frobenius_colE, mxdot_le, ler_mxdot, frobeniusD, frobeniusB, ler_frobeniusB, frobenius_entry, frobenius_mulmx, frobenius_orthogonalmxl, frobenius_orthogonalmxr
- GaussianAnalysis.matrix.real_spectral: mx_norm_le_frobenius, frobenius_le_mx_norm, compact_unit_sphere, rayleigh_max
- GaussianAnalysis.matrix.whitening: frobenius_whitening_mx, whitening_exists
- GaussianAnalysis.matrix.opnorm: opnorm, opnorm_has_sup, opnorm_ub, opnorm_le, opnorm_le_frobenius, frobenius_mulmx_opnorm, opnorm_leP, frobenius_mulmx_mx_opnorm, mxdot_opnorm, mxdot_delta_opnorm, mx_norm_le_opnorm, opnorm_bilinearP
- GaussianAnalysis.matrix.lambda_max: lambda_max_ubound, lambda_max_form, lambda_max_lipschitz_frobenius, opnorm_lambda_max
- GaussianAnalysis.matrix.psd_splitting: frobenius_sqr_sym, two_matrix_split, frobenius_compress_le, frobenius_sum_psd_le, psd_splitting_rel, psd_splitting
- GaussianAnalysis.matrix.nets: is_net, unit_ball, unit_sphere, opnorm_net, mxdot_net_bound, opnorm_net_sphere, opnorm_net_bilinear, form_unit_ball_le, opnorm_net_sym, frobenius_col_sqr, grid_code_dist, sum_abs_col_le, grid_net, net_exists, unit_ball_net, unit_sphere_net
- GaussianAnalysis.matrix.random_opnorm: mxdot_psd_le, opnorm_sym_part_net, unit_ball_quarter_net, opnorm_sum_subexponential
- GaussianAnalysis.matrix.covering: colmax, colmax_col, colmax_le, colmax_le_opnorm, colmax_le_frobenius, frobenius_mxvec_mx, gopnorm_mean, frob_sep, colmax_sep, dual_ball_covering, matrix_small_ball
- GaussianAnalysis.matrix.von_neumann: spec_lipschitz, spec_stat_lipschitz
- GaussianAnalysis.matrix.psd_part: psd_part_nearest, psd_part_nonexpansive, frobenius_psd_part_shift
- GaussianAnalysis.matrix.nuclear: frobenius_le_opnorm, nuclear_has_sup, mxdot_le_nuclear, frobenius_sqr_le_nuclear, frobenius_le_nuclear, nuclear_le_frobenius, nuclear_outer, nuclear_spectral, range_duality
- GaussianAnalysis.matrix.condition_cone: cond_support_proj
- GaussianAnalysis.matrix.trace_projection: trace_argmax_lipschitz, trace_argmax_norm
- GaussianAnalysis.matrix.tensor_packing: frobenius_sum_le, almost_orthogonal_sum_le, almost_orthogonal_card_le, frobenius_trmx_isometry, frobenius_isometry_le, large_projection_cluster_card, large_projection_card, maximal_separated_subset, frobenius_rowperp_le, frobenius_rowproj, frobenius_tensor, frobenius_mxcoef_sqr, frobenius_mxcoef_le, frobenius_outer, frobenius_rowperp_compress_le, mxcoef_compress_near, frobenius_sum_near, sudakov_mx_series, separated_card_sudakov, tensor_packing
- GaussianAnalysis.probability.subgaussian_matrix: opnorm_lip, measurable_opnorm, opnorm_tail_mgf, subgaussian_opnorm_tail
- GaussianAnalysis.probability.small_ball_method: rat_approx_rV, dense_seq_rV, mxdot_form_lipschitz, small_ball_linear
- GaussianAnalysis.probability.hanson_wright: entry_le_opnorm, hanson_wright_subexponential
- GaussianAnalysis.random_matrix.goe: gauss_frobenius_mean, frobenius_goe_mx, goe_opnorm_lipschitz, goe_clip_lipschitz
- GaussianAnalysis.random_matrix.goe_edge: goe_form_max_mean, lambda_max_net_le, goe_lambda_max_lipschitz, goe_lambda_maxN_lipschitz
- GaussianAnalysis.random_matrix.wigner: goe_stat_lipschitz, continuous_goe_stat
- GaussianAnalysis.random_matrix.restricted_isometry: maxnorm, cross_event, cross_tail, sparse_net, diag_part_le, gram_off_rip, tuple_mx_rip, gram_off_rip2, gram_off_ball, rip_good, tuple_mx_blocks, sphere_net_spec, sphere_netP, tuple_submx_net, sparse_norm_subgaussian
- GaussianAnalysis.random_matrix.matrix_series: mxtrace_mul_psd_le, opnorm_le_sym_dilation, series_opnorm_lipschitz
- GaussianAnalysis.random_matrix.goe_entries: frobenius_goe_coef_diag, goe_mx_offdiag_tail, measurable_goe_opnorm_ge
- GaussianAnalysis.comparison.gauss_linear: gauss_mxdot, ge0_integral_gauss_mxdot, integrable_gauss_mxdot
- and 209 more
forall [R : rcfType] [m n : nat] (A : 'M_(m, n)), 0 <= frobenius A
Statement as written in the source
Lemma frobenius_ge0 m n (A : 'M[R]_(m, n)) : 0 <= frobenius A.
Used by 130 declarations in 34 files
- GaussianAnalysis.gaussian.lebesgue_rV: lebesgue_rV_ball_le
- this file: mxdot_le, frobeniusD, frobenius_mulmx
- GaussianAnalysis.matrix.real_spectral: mx_norm_le_frobenius
- GaussianAnalysis.matrix.opnorm: opnorm_has_sup, opnorm_le_frobenius, frobenius_mulmx_opnorm, opnorm_leP, frobenius_mulmx_mx_opnorm, mxdot_opnorm, opnorm_bilinearP, opnorm_symP
- GaussianAnalysis.matrix.nets: mxdot_net_bound, opnorm_net_sphere, form_unit_ball_le, sum_abs_col_le, grid_net
- GaussianAnalysis.matrix.covering: colmax_ge0
- GaussianAnalysis.matrix.psd_part: psd_part_nonexpansive
- GaussianAnalysis.matrix.nuclear: nuclear_has_sup, mxdot_le_nuclear, frobenius_le_nuclear, nuclear_le_frobenius, nuclear_eq0, nuclear_outer
- GaussianAnalysis.matrix.condition_cone: cond_support_ge0
- GaussianAnalysis.matrix.trace_projection: trace_argmax_lipschitz
- GaussianAnalysis.matrix.tensor_packing: almost_orthogonal_sum_le, almost_orthogonal_card_le, frobenius_isometry_le, large_projection_cluster_card, frobenius_rowperp_le, frobenius_mxcoef_le, opnorm_compress_gram, trace_compress_gram, mxcoef_compress_near, sudakov_mx_series, tensor_packing
- GaussianAnalysis.probability.subgaussian_matrix: subgaussian_opnorm_tail
- GaussianAnalysis.probability.small_ball_method: mxdot_form_lipschitz, small_ball_linear
- GaussianAnalysis.probability.hanson_wright: gauss_chaos_mgf, opnorm_diag01
- GaussianAnalysis.random_matrix.restricted_isometry: measurable_cross_event, cross_tail, sparse_net, diag_part_le, gram_off_rip2, gram_off_ball, sparse_norm_subgaussian
- GaussianAnalysis.random_matrix.matrix_series: mxdot_mulmx_opnorm_le, opnorm_block_diag_le, series_opnorm_lipschitz
- GaussianAnalysis.random_matrix.goe_entries: opnorm_diag_mx_le
- GaussianAnalysis.comparison.gauss_smoothing: lipschitz_frobenius_continuous, lipschitz_frobenius_grad, integrable_gauss_frobenius
- GaussianAnalysis.comparison.gauss_concentration: herbst_DFdot, M0, lipschitz_frobenius_bound, integrable_gauss_lipschitz
- GaussianAnalysis.comparison.escape: escape_inf_le, escape_inf_ge0, rmax_net_ge, minmax_bil_le, gordon_escape, minmax_bil_sph_le, rmax_net_width, gordon_minmax, frobenius_proj_le, gauss_opnorm_mean, gauss_frobenius_mean_le, gauss_proj_mean_ge
- GaussianAnalysis.comparison.cgmt: integrable_infsupX, integrable_infsupY, infsup_compare, frobenius_lsubmx_le, frobenius_rsubmx_le, frobenius_hsub_add, mxdot_mulmx_le, cgmt_aux_lipschitz, mx_norm_frobenius, continuous_frobenius_mulmx, escape_inf_lip, escape_inf_minimax, rho0, dotg, doth, Xp_b, Xp_x, Xp_y, Xp_w, Yp_b, Yp_x, Yp_y, Yp_z, low_X, up_X, up_Y
- GaussianAnalysis.comparison.cone_escape: dot_le1, cone_sup_proj, cgmt_aux_cone_zero, cgmt_aux_cone_zero_lt
- GaussianAnalysis.comparison.sudakov: mx_norm_frob, sudakov_minoration, dual_sudakov
- GaussianAnalysis.comparison.gauss_law: Ey0, lipschitz_frobenius_mulmx, gauss_law_lipschitz, setI_closed_lipschitz_pos, lipschitz_pos_agree
- GaussianAnalysis.convex.self_concordant: sc_function_continuous
- GaussianAnalysis.convex.logdet_barrier: posdefmx_open
- GaussianAnalysis.convex.feature_moments: quad_le_frobenius, reg_int_quad, quad_sqr_le
- GaussianAnalysis.convex.gauss_feature: gauss_mxdot_moments, opnorm_sqr_le, gauss_regular_feature
- GaussianAnalysis.convex.moreau: proj_exists, proj_nonexpansive, cone_proj_support
- GaussianAnalysis.convex.feature_mixture: moment4_int_quad
- GaussianAnalysis.fourier.charfun_rV: measurable_ball_rV, gauss_frobenius_ge
- GaussianAnalysis.fourier.small_ball: contraction_trmx, cf_rV_regularized_le
- GaussianAnalysis.fourier.inversion: lipschitz_add_gauss
- GaussianApplications.SKGap.Disorder: frobenius_sk_coupling_le
Statement as written in the source
Used by 87 declarations in 35 files
- GaussianAnalysis.gaussian.lebesgue_rV: lebesgue_rV_ball_le
- this file: mxdot_le, frobeniusD, frobenius_mulmx
- GaussianAnalysis.matrix.real_spectral: rayleigh_max
- GaussianAnalysis.matrix.opnorm: frobenius_mulmx_mx_opnorm, opnorm_bilinearP, opnorm_symP, opnorm_spectral
- GaussianAnalysis.matrix.lambda_max: lambda_max_form
- GaussianAnalysis.matrix.psd_splitting: frobenius_sqr_sym, two_matrix_split, frobenius_compress_le, frobenius_sum_psd_le, psd_splitting_rel
- GaussianAnalysis.matrix.nets: opnorm_net_sphere, form_unit_ball_le, frobenius_col_sqr
- GaussianAnalysis.matrix.psd_part: psd_part_nonexpansive, frobenius_psd_part_shift
- GaussianAnalysis.matrix.nuclear: frobenius_sqr_le_nuclear, nuclear_outer
- GaussianAnalysis.matrix.condition_cone: cond_support_sqr
- GaussianAnalysis.matrix.trace_projection: trace_argmax_lipschitz
- GaussianAnalysis.matrix.tensor_packing: almost_orthogonal_card_le, frobenius_isometry_le, large_projection_cluster_card, frobenius_rowperp_le, frobenius_mxcoef_sqr, frobenius_mxcoef_le, opnorm_compress_gram, trace_compress_gram, tensor_packing
- GaussianAnalysis.probability.subgaussian_matrix: subgaussian_opnorm_tail
- GaussianAnalysis.probability.hanson_wright: gauss_chaos_mgf, opnorm_diag01, hanson_wright_subexponential
- GaussianAnalysis.random_matrix.goe: gauss_frobenius_mean
- GaussianAnalysis.random_matrix.goe_edge: goe_form_max_mean
- GaussianAnalysis.random_matrix.restricted_isometry: measurable_cross_event, cross_tail, sparse_net, diag_part_le, gram_off_rip, tuple_mx_rip, tuple_mx_blocks, sparse_norm_subgaussian
- GaussianAnalysis.random_matrix.matrix_series: mxdot_mulmx_opnorm_le, opnorm_block_diag_le
- GaussianAnalysis.random_matrix.goe_entries: opnorm_diag_mx_le, frobenius_goe_coef_diag, goe_mx_offdiag_tail
- GaussianAnalysis.comparison.gauss_smoothing: lipschitz_frobenius_grad
- GaussianAnalysis.comparison.escape: sq1, sq1, rmax_net_ge, frobenius_proj_le, gwidth_range_sphere, gauss_frobenius_mean_le, gwidth_sphere, gauss_sqr_mulmx, gauss_proj_mean_ge
- GaussianAnalysis.comparison.cgmt: incr_var_gamma, gordon_gamma, frobenius_hsub_sqr, unit_dir, escape_inf_minimax
- GaussianAnalysis.comparison.cone_escape: cone_sup_proj
- GaussianAnalysis.comparison.sudakov: sudakov_minoration, dual_sudakov
- GaussianAnalysis.convex.logdet_barrier: posdefmx_open
- GaussianAnalysis.convex.feature_moments: quad_le_frobenius, form_le_opnorm
- GaussianAnalysis.convex.gauss_feature: opnorm_sqr_le, gauss_regular_feature
- GaussianAnalysis.convex.barrier_lindeberg: loo_compare
- GaussianAnalysis.convex.moreau: proj_nonexpansive, cone_proj_support
- GaussianAnalysis.convex.feature_mixture: mixture_regular_feature
- GaussianAnalysis.fourier.charfun_rV: cf_rV_gauss, measurable_ball_rV, gauss_frobenius_ge
- GaussianAnalysis.fourier.small_ball: contraction_trmx, cf_rV_regularized_le
- GaussianAnalysis.fourier.inversion: lipschitz_add_gauss
- GaussianApplications.SKGap.Disorder: frobenius_sk_coupling_le
- GaussianApplications.SKGap.Poincare: pair_quad_le
forall [R : rcfType] [m n : nat] (A : 'M_(m, n)), (frobenius A == 0) = (A == 0)
Statement as written in the source
Lemma frobenius_eq0 m n (A : 'M[R]_(m, n)) : (frobenius A == 0) = (A == 0).
Used by 7 declarations in 4 files
- GaussianAnalysis.matrix.nuclear: nuclear_eq0
- GaussianAnalysis.comparison.gauss_linear: gauss_mxdot, integral_gauss_expR_mxdot, gauss_mxdot_upper_tail, gauss_mxdot_abs_tail
- GaussianAnalysis.fourier.charfun_rV: cf_rV_gauss
- GaussianAnalysis.fourier.small_ball: cf_rV_regularized_le
forall [R : rcfType] [m n : nat] (A : 'M_(m, n)), (0 < frobenius A) = (A != 0)
Statement as written in the source
Lemma frobenius_gt0 m n (A : 'M[R]_(m, n)) : (0 < frobenius A) = (A != 0).
Used by 18 declarations in 12 files
- GaussianAnalysis.matrix.real_spectral: rayleigh_max
- GaussianAnalysis.matrix.opnorm: frobenius_mulmx_opnorm
- GaussianAnalysis.matrix.lambda_max: lambda_max_form
- GaussianAnalysis.matrix.nets: opnorm_net_sphere, form_unit_ball_le
- GaussianAnalysis.matrix.trace_projection: trace_argmax_lipschitz
- GaussianAnalysis.probability.hanson_wright: hanson_wright_subexponential
- GaussianAnalysis.random_matrix.restricted_isometry: cross_tail, gram_off_rip
- GaussianAnalysis.comparison.escape: rmax_net_ge, range_sphere0, gwidth_range_sphere, gwidth_sphere
- GaussianAnalysis.comparison.cgmt: unit_dir
- GaussianAnalysis.comparison.cone_escape: cone_sup_dot
- GaussianAnalysis.convex.moreau: proj_nonexpansive, cone_proj_support
- GaussianAnalysis.fourier.small_ball: vector_small_ball_of
forall (R : rcfType) (m n : nat), frobenius (0 : 'M_(m, n)) = 0
Statement as written in the source
Lemma frobenius0 m n : frobenius (0 : 'M[R]_(m, n)) = 0.
Used by 31 declarations in 16 files
- GaussianAnalysis.matrix.opnorm: opnorm_has_sup, opnorm_ge0, frobenius_mulmx_opnorm, opnorm0
- GaussianAnalysis.matrix.nets: unit_ball0, opnorm_net_sphere
- GaussianAnalysis.matrix.covering: dual_ball_covering
- GaussianAnalysis.matrix.trace_projection: trace_argmax_lipschitz
- GaussianAnalysis.matrix.tensor_packing: frobenius_sum_le, maximal_separated_subset
- GaussianAnalysis.random_matrix.goe: gauss_frobenius_mean
- GaussianAnalysis.random_matrix.restricted_isometry: cross_tail, tuple_mx_blocks
- GaussianAnalysis.random_matrix.matrix_series: series_opnorm_lipschitz
- GaussianAnalysis.random_matrix.goe_entries: goe_mx_diag_tail, goe_mx_offdiag_tail
- GaussianAnalysis.comparison.gauss_linear: gauss_mxdot, integral_gauss_expR_mxdot
- GaussianAnalysis.comparison.escape: rmax_net_ge, gwidth_range_sphere, gwidth_sphere
- GaussianAnalysis.comparison.cgmt: unit_dir, low_aux
- GaussianAnalysis.comparison.cone_escape: cone_sup_le, cone_sup_ge0, cone_sup_attained, cone_sup_dot
- GaussianAnalysis.comparison.sudakov: sudakov_minoration
- GaussianAnalysis.convex.moreau: proj_nonexpansive, cone_proj_support
- GaussianAnalysis.fourier.small_ball: cf_rV_regularized_le
Statement as written in the source
Used by 26 declarations in 16 files
- this file: frobeniusN
- GaussianAnalysis.matrix.opnorm: frobenius_mulmx_opnorm, opnormZ
- GaussianAnalysis.matrix.nets: opnorm_net_sphere, form_unit_ball_le
- GaussianAnalysis.matrix.covering: colmaxZ
- GaussianAnalysis.matrix.condition_cone: cond_supportZ
- GaussianAnalysis.matrix.tensor_packing: large_projection_cluster_card, frobenius_sum_near
- GaussianAnalysis.random_matrix.goe: frobenius_goe_mx
- GaussianAnalysis.random_matrix.matrix_series: series_opnorm_lipschitz
- GaussianAnalysis.comparison.gauss_smoothing: lipschitz_frobenius_grad, gauss_smooth_close
- GaussianAnalysis.comparison.escape: rmax_net_ge, range_sphere0, gwidth_range_sphere, gwidth_sphere
- GaussianAnalysis.comparison.cgmt: unit_dir, escape_inf_minimax
- GaussianAnalysis.comparison.cone_escape: cone_sup_dot, cgmt_aux_cone_zero
- GaussianAnalysis.comparison.gauss_law: gauss_smooth_partial_stein
- GaussianAnalysis.fourier.charfun_rV: lebesgue_rV_ball_scale, ball_le_cf_rV
- GaussianAnalysis.fourier.small_ball: ball_le_add_gauss
- GaussianAnalysis.fourier.inversion: lipschitz_add_gauss
Statement as written in the source
Used by 28 declarations in 11 files
- this file: frobeniusB, ler_frobeniusB
- GaussianAnalysis.matrix.nets: grid_net
- GaussianAnalysis.matrix.covering: colmaxN, dual_ball_covering
- GaussianAnalysis.matrix.tensor_packing: large_projection_cluster_card, maximal_separated_subset, frobenius_sum_near
- GaussianAnalysis.probability.subgaussian_matrix: opnorm_lip
- GaussianAnalysis.probability.small_ball_method: dense_seq_rV
- GaussianAnalysis.random_matrix.goe_edge: goe_lambda_maxN_lipschitz
- GaussianAnalysis.comparison.escape: gwidth_lipschitz, gwidth_norm, escape_inf_lipschitz, minmax_bil_le, minmax_sph_lipschitz, minmax_bil_sph_le, sym_sphere_net, opnorm_lipschitz
- GaussianAnalysis.comparison.cgmt: infsup_net, cgmt_auxNl, cgmt_aux_lipschitz, escape_inf_lip, escape_inf_minimax, low_aux, cgmt_lower
- GaussianAnalysis.comparison.cone_escape: cone_sup_lipschitz
- GaussianAnalysis.convex.logdet_barrier: rel_open_convex_pd_slice2
Statement as written in the source
Used by 34 declarations in 10 files
- GaussianAnalysis.matrix.covering: matrix_small_ball
- GaussianAnalysis.matrix.tensor_packing: trace_compress_gram, frobenius_outer, frobenius_rowperp_compress_le, mxcoef_compress_near, sudakov_mx_series, tensor_packing
- GaussianAnalysis.random_matrix.goe: frobenius_goe_mx
- GaussianAnalysis.random_matrix.goe_edge: goe_form_max_mean
- GaussianAnalysis.random_matrix.restricted_isometry: sparse_norm_subgaussian
- GaussianAnalysis.comparison.escape: dot_le, gordon_escape, minmax_sph_le, minmax_sph_lipschitz, minmax_bil_sph_le, rmax_net_width, gwidth_range_sphere, minmax_sph_range, gauss_opnorm_mean, gwidth_sphere, gauss_proj_mean_ge
- GaussianAnalysis.comparison.cgmt: unit_dir, cgmt_aux_lipschitz, closed_bounded_compact_cV, dotg, doth, up_Y, cgmt_aux_tr_set, tr_set_bounded
- GaussianAnalysis.comparison.cone_escape: dot_le1, cone_sup_tr_setE, tr_set_norm_ge
- GaussianAnalysis.convex.feature_moments: form_le_opnorm
- GaussianAnalysis.convex.gauss_feature: gauss_regular_feature
forall [R : rcfType] [n : nat] (u : 'rV_n), frobenius u = Num.ExtraDef.sqrtr ((u *m u^T) 0 0)
Statement as written in the source
Lemma frobenius_rowE n (u : 'rV[R]_n) : frobenius u = Num.sqrt ((u *m u^T) 0 0).
forall [R : rcfType] [n : nat] (x : 'cV_n), frobenius x = Num.ExtraDef.sqrtr ((x^T *m x) 0 0)
Statement as written in the source
Lemma frobenius_colE n (x : 'cV[R]_n) : frobenius x = Num.sqrt ((x^T *m x) 0 0).
Statement as written in the source
Used by 21 declarations in 12 files
- this file: ler_mxdot
- GaussianAnalysis.matrix.opnorm: mxdot_opnorm
- GaussianAnalysis.matrix.nuclear: mxdot_le_nuclear
- GaussianAnalysis.matrix.tensor_packing: almost_orthogonal_sum_le, frobenius_isometry_le, tensor_packing
- GaussianAnalysis.probability.small_ball_method: mxdot_form_lipschitz
- GaussianAnalysis.random_matrix.restricted_isometry: gram_off_rip2, tuple_mx_blocks
- GaussianAnalysis.comparison.cgmt: mxdot_mulmx_le, cgmt_aux_lipschitz, dotg, doth, up_Y
- GaussianAnalysis.comparison.cone_escape: cone_sup_attained
- GaussianAnalysis.comparison.brascamp_lieb: gauss_ibp_unit, mxdot_unit_le1, mxdot_le_mx_norm
- GaussianAnalysis.convex.self_concordant: sc_function_continuous
- GaussianAnalysis.convex.logdet_barrier: posdefmx_open
- GaussianAnalysis.convex.feature_moments: quad_le_frobenius
Statement as written in the source
Used by 26 declarations in 14 files
- this file: frobeniusD
- GaussianAnalysis.matrix.psd_part: psd_part_nonexpansive
- GaussianAnalysis.matrix.nuclear: nuclear_has_sup, nuclear_le_frobenius
- GaussianAnalysis.matrix.trace_projection: trace_argmax_lipschitz
- GaussianAnalysis.random_matrix.goe_edge: goe_form_max_mean
- GaussianAnalysis.random_matrix.restricted_isometry: diag_part_le
- GaussianAnalysis.comparison.gauss_concentration: herbst_DFdot
- GaussianAnalysis.comparison.escape: dot1, dot1, dot_le, rmax_net_ge, minmax_bil_le, rmax_net_width, frobenius_proj_le, gwidth_range_sphere, gauss_opnorm_mean, gwidth_sphere
- GaussianAnalysis.comparison.cgmt: gordon_gamma, low_X
- GaussianAnalysis.comparison.cone_escape: dot_le1
- GaussianAnalysis.convex.self_concordant: sc_function_continuous
- GaussianAnalysis.convex.gauss_feature: opnorm_sqr_le
- GaussianAnalysis.convex.moreau: proj_nonexpansive, cone_proj_support
- GaussianAnalysis.fourier.small_ball: contraction_trmx
Stated in the README together with mxdot.
Statement as written in the source
Used by 21 declarations in 13 files
- this file: frobeniusB, ler_frobeniusB
- GaussianAnalysis.matrix.opnorm: opnormD
- GaussianAnalysis.matrix.nets: opnorm_net, grid_net
- GaussianAnalysis.matrix.covering: colmaxD
- GaussianAnalysis.matrix.tensor_packing: frobenius_sum_le, large_projection_cluster_card, mxcoef_compress_near, frobenius_sum_near, tensor_packing
- GaussianAnalysis.probability.small_ball_method: dense_seq_rV, small_ball_linear
- GaussianAnalysis.random_matrix.goe: frobenius_goe_mx
- GaussianAnalysis.random_matrix.restricted_isometry: tuple_mx_blocks
- GaussianAnalysis.random_matrix.matrix_series: series_opnorm_lipschitz
- GaussianAnalysis.comparison.escape: escape_inf_lipschitz, minmax_bil_le
- GaussianAnalysis.comparison.cgmt: escape_inf_lip
- GaussianAnalysis.fourier.charfun_rV: ball_le_cf_rV
- GaussianAnalysis.fourier.small_ball: ball_le_add_gauss
Statement as written in the source
Used by 2 declarations in 2 files
- GaussianAnalysis.random_matrix.restricted_isometry: gram_off_ball
- GaussianAnalysis.convex.moreau: proj_exists
forall [R : rcfType] [m n : nat] (A B : 'M_(m, n)), `|frobenius A - frobenius B| <= frobenius (A - B)
Statement as written in the source
Used by 12 declarations in 4 files
- GaussianAnalysis.comparison.gauss_smoothing: integrable_gauss_frobenius
- GaussianAnalysis.comparison.escape: gauss_frobenius_mean_le, gauss_proj_mean_ge
- GaussianAnalysis.comparison.cgmt: cgmt_aux_lipschitz, continuous_frobenius_mulmx, Xp_x, Xp_y, Yp_x, Yp_y, cgmt_lower, cgmt_upper
- GaussianAnalysis.comparison.cone_escape: F_lip
forall [R : rcfType] [m n : nat] (A : 'M_(m, n)) (i : 'I_m) (j : 'I_n), `|A i j| <= frobenius A
Statement as written in the source
Lemma frobenius_entry m n (A : 'M[R]_(m, n)) i j : `|A i j| <= frobenius A.
Used by 13 declarations in 6 files
- GaussianAnalysis.matrix.real_spectral: mx_norm_le_frobenius
- GaussianAnalysis.random_matrix.matrix_series: series_opnorm_lipschitz
- GaussianAnalysis.comparison.cgmt: mx_norm_frobenius, ng, low_X, up_X
- GaussianAnalysis.comparison.sudakov: mx_norm_frob, gauss_max_lower, sudakov_minoration
- GaussianAnalysis.comparison.gauss_law: gauss_smooth_partial_bounded, gauss_smooth_partial_lipschitz, measurable_lipschitz_pos
- GaussianAnalysis.convex.moreau: proj_exists
forall [R : rcfType] [m n p : nat] (A : 'M_(m, n)) (B : 'M_(n, p)), frobenius (A *m B) <= frobenius A * frobenius B
Stated in the README together with mxdot.
Statement as written in the source
Used by 16 declarations in 8 files
- GaussianAnalysis.matrix.opnorm: opnorm_has_sup, opnorm_le_frobenius
- GaussianAnalysis.probability.small_ball_method: mxdot_form_lipschitz
- GaussianAnalysis.comparison.escape: escape_inf_lipschitz, escape_inf_norm, minmax_bil_le, minmax_sph_le, minmax_sph_lipschitz, minmax_bil_sph_le
- GaussianAnalysis.comparison.cgmt: mxdot_mulmx_le, continuous_frobenius_mulmx, escape_inf_lip
- GaussianAnalysis.comparison.gauss_law: lipschitz_frobenius_mulmx
- GaussianAnalysis.convex.self_concordant: sc_function_continuous
- GaussianAnalysis.convex.logdet_barrier: posdefmx_open
- GaussianAnalysis.convex.feature_moments: quad_le_frobenius
Variable R : comUnitRingType. Implicit Types m n : nat.
forall {R : comUnitRingType} {n : nat}, qualifier 0 'M_nDefinition orthogonalmx {n} := [qualify M : 'M[R]_n | M *m M^T == 1%:M].
The orthogonal matrices (M M^T = 1). Multiplying by an orthogonal matrix, on either side, preserves the Frobenius inner product and norm.
Used by 59 declarations in 14 files
- this file: orthogonalmx_key, orthogonalmxP, orthogonalmxT, trmx_orthogonal, orthogonalmx1, mul_orthogonalmx, orthogonalmx_unit, invmx_orthogonal, orthogonal_block_mx, perm_mx_orthogonal, mxdot_orthogonalmxl, mxdot_orthogonalmxr, frobenius_orthogonalmxl, frobenius_orthogonalmxr
- GaussianAnalysis.matrix.real_spectral: householder_orthogonal, symmetric_spectral, spectral_eigenvector, orthogonalmx_row_unit, spectral_trace, spectral_mxdot, spectral_form_le, spectral_form_ge, spectral_psd, spectral_form_abs, spectral_exp, ex_sym_spectral, sym_spectralmx_orthogonal
- GaussianAnalysis.matrix.opnorm: opnorm_orthogonalmxl, opnorm_orthogonalmxr, opnorm_spectral
- GaussianAnalysis.matrix.psd_splitting: spectral_nonneg_proj
- GaussianAnalysis.matrix.von_neumann: spec_decomposition, orthogonal_sqr_row, orthogonal_sqr_col, von_neumann_trace
- GaussianAnalysis.matrix.psd_part: psd_conj, psd_nearest, psd_partE, psd_part_conj, spec_shift_decomposition, char_poly_conj_diag, spec_conj_diag, mxdot_psd_part_shift
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.nuclear: nuclear_spectral
- GaussianAnalysis.matrix.condition_cone: cond_clip_cone, cond_clip_energy
- GaussianAnalysis.matrix.trace_projection: mxdot_conjmx, mxtrace_conj, trace_scale_conj, trace_argmax_conj
- GaussianAnalysis.random_matrix.goe_rotation: mxdot_conj, conj_mx_orthogonal, goe_conj_integral, conj_equivariant, goe_equiv_form
- GaussianAnalysis.comparison.brascamp_lieb: gauss_ibp_unit
- GaussianAnalysis.convex.logdet_barrier: posdefmx_spectral
- GaussianAnalysis.convex.gauss_feature: gauss_quad_moments
forall (R : comUnitRingType) (n : nat), pred_key orthogonalmx
Statement as written in the source
Fact orthogonalmx_key n : pred_key (@orthogonalmx n).
Used by 1 declaration in 1 file
- this file: orthogonalmx_keyed
Canonical orthogonalmx_keyed n := KeyedQualifier (orthogonalmx_key n).
forall [R : comUnitRingType] [n : nat] (M : 'M_n), reflect (M *m M^T = 1%:M) (M \is orthogonalmx)
Statement as written in the source
Lemma orthogonalmxP n (M : 'M[R]_n) : reflect (M *m M^T = 1%:M) (M \is orthogonalmx).
Used by 34 declarations in 15 files
- this file: orthogonalmxT, trmx_orthogonal, orthogonalmx1, mul_orthogonalmx, orthogonalmx_unit, invmx_orthogonal, orthogonal_block_mx, perm_mx_orthogonal, mxdot_orthogonalmxr
- GaussianAnalysis.matrix.real_spectral: householder_orthogonal, spectral_eigenvector, orthogonalmx_row_unit, spectral_trace, spectral_exp
- GaussianAnalysis.matrix.whitening: whitening_mxP
- GaussianAnalysis.matrix.opnorm: opnorm_orthogonalmxr
- GaussianAnalysis.matrix.psd_splitting: spectral_nonneg_proj
- GaussianAnalysis.matrix.von_neumann: orthogonal_sqr_row
- GaussianAnalysis.matrix.psd_part: spec_shift_decomposition, char_poly_conj_diag, mxdot_psd_part_shift
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.nuclear: nuclear_spectral
- GaussianAnalysis.matrix.trace_projection: trace_scale_conj, trace_argmax_conj
- GaussianAnalysis.matrix.tensor_packing: select_rows_orth, spectral_rowperp_coord
- GaussianAnalysis.random_matrix.goe_rotation: mxdot_conj, conj_mx_orthogonal
- GaussianAnalysis.convex.logdet_barrier: congruence_diag, logdet_barrier_ge0, logdet_barrier2_ge0
- GaussianAnalysis.convex.minimizers: vspace_orthonormal
- GaussianAnalysis.convex.gauss_feature: gauss_quad_moments
forall [R : comUnitRingType] [n : nat] [M : 'M_n], M \is orthogonalmx -> M^T *m M = 1%:M
Statement as written in the source
Lemma orthogonalmxT n (M : 'M[R]_n) : M \is orthogonalmx -> M^T *m M = 1%:M.
Used by 12 declarations in 9 files
- this file: mxdot_orthogonalmxl
- GaussianAnalysis.matrix.real_spectral: spectral_exp
- GaussianAnalysis.matrix.psd_splitting: spectral_nonneg_proj
- GaussianAnalysis.matrix.trace_projection: mxtrace_conj
- GaussianAnalysis.random_matrix.goe_rotation: goe_conj_integral
- GaussianAnalysis.random_matrix.matrix_series: mxtrace_sandwich_le
- GaussianAnalysis.comparison.brascamp_lieb: gauss_ibp_unit
- GaussianAnalysis.convex.logdet_barrier: congruence_diag, logdet_barrier_ge0, logdet_barrier2_ge0
- GaussianAnalysis.convex.minimizers: vspace_orthonormal, posdefmx_unit
forall [R : comUnitRingType] [n : nat] (M : 'M_n), (M^T \is orthogonalmx) = (M \is orthogonalmx)
Statement as written in the source
Lemma trmx_orthogonal n (M : 'M[R]_n) : (M^T \is orthogonalmx) = (M \is orthogonalmx).
Used by 19 declarations in 11 files
- GaussianAnalysis.matrix.real_spectral: spectral_mxdot
- GaussianAnalysis.matrix.opnorm: opnorm_orthogonalmxr, opnorm_symP
- GaussianAnalysis.matrix.random_opnorm: mxdot_psd_le
- GaussianAnalysis.matrix.von_neumann: orthogonal_sqr_col, von_neumann_trace
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_part_conj, psd_part_moreau, spec_shift_decomposition, char_poly_conj_diag, mxdot_psd_part_shift
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.nuclear: nuclear_spectral
- GaussianAnalysis.matrix.trace_projection: mxdot_conjmx, trace_argmax_conj
- GaussianAnalysis.random_matrix.goe_rotation: goe_diag_var_tail
- GaussianAnalysis.random_matrix.matrix_series: mxtrace_mul_psd_le
- GaussianAnalysis.convex.gauss_feature: gauss_quad_moments
forall (R : comUnitRingType) (n : nat), (1%:M : 'M_n) \is orthogonalmx
Statement as written in the source
Lemma orthogonalmx1 n : (1%:M : 'M[R]_n) \is orthogonalmx.
Used by 2 declarations in 1 file
- GaussianAnalysis.matrix.real_spectral: symmetric_spectral, ex_sym_spectral
forall [R : comUnitRingType] [n : nat] [A B : 'M_n], A \is orthogonalmx -> B \is orthogonalmx -> A *m B \is orthogonalmx
Statement as written in the source
Lemma mul_orthogonalmx n (A B : 'M[R]_n) : A \is orthogonalmx -> B \is orthogonalmx -> A *m B \is orthogonalmx.
Used by 4 declarations in 3 files
- GaussianAnalysis.matrix.real_spectral: symmetric_spectral
- GaussianAnalysis.matrix.von_neumann: spec_decomposition, von_neumann_trace
- GaussianAnalysis.matrix.psd_part: psd_part_conj
forall [R : comUnitRingType] [n : nat] [M : 'M_n], M \is orthogonalmx -> M \in unitmx
Statement as written in the source
Lemma orthogonalmx_unit n (M : 'M[R]_n) : M \is orthogonalmx -> M \in unitmx.
Used by 3 declarations in 2 files
- this file: invmx_orthogonal
- GaussianAnalysis.convex.logdet_barrier: congruence_diag, logdet_barrier2_ge0
forall [R : comUnitRingType] [n : nat] [M : 'M_n], M \is orthogonalmx -> invmx M = M^T
Statement as written in the source
Lemma invmx_orthogonal n (M : 'M[R]_n) : M \is orthogonalmx -> invmx M = M^T.
forall [R : comUnitRingType] [m n : nat] [P : 'M_m] [Q : 'M_n], P \is orthogonalmx -> Q \is orthogonalmx -> block_mx P 0 0 Q \is orthogonalmx
Statement as written in the source
Lemma orthogonal_block_mx m n (P : 'M[R]_m) (Q : 'M[R]_n) : P \is orthogonalmx -> Q \is orthogonalmx -> block_mx P 0 0 Q \is orthogonalmx.
Used by 1 declaration in 1 file
- GaussianAnalysis.matrix.real_spectral: symmetric_spectral
forall (R : comUnitRingType) [n : nat] (s : {perm 'I_n}), perm_mx s \is orthogonalmx
Statement as written in the source
Lemma perm_mx_orthogonal n (s : 'S_n) : perm_mx s \is orthogonalmx.
Used by 1 declaration in 1 file
- GaussianAnalysis.matrix.von_neumann: spec_decomposition
forall [R : comUnitRingType] [m n : nat] [P : 'M_m] (A B : 'M_(m, n)), P \is orthogonalmx -> mxdot (P *m A) (P *m B) = mxdot A B
Stated in the README together with orthogonalmx.
Statement as written in the source
Lemma mxdot_orthogonalmxl m n (P : 'M[R]_m) (A B : 'M[R]_(m, n)) : P \is orthogonalmx -> mxdot (P *m A) (P *m B) = mxdot A B.
Used by 14 declarations in 10 files
- this file: frobenius_orthogonalmxl
- GaussianAnalysis.matrix.real_spectral: spectral_mxdot, spectral_form_le, spectral_form_ge
- GaussianAnalysis.matrix.opnorm: opnorm_symP
- GaussianAnalysis.matrix.spectral_gap: psd_square_gap
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_part_moreau, mxdot_psd_part_shift
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.trace_projection: mxdot_conjmx
- GaussianAnalysis.matrix.tensor_packing: spectral_rowperp_form_le
- GaussianAnalysis.random_matrix.goe_rotation: goe_diag_var_tail
- GaussianAnalysis.convex.gauss_feature: gauss_quad_moments
forall [R : comUnitRingType] [m n : nat] [P : 'M_n] (A B : 'M_(m, n)), P \is orthogonalmx -> mxdot (A *m P) (B *m P) = mxdot A B
Statement as written in the source
Lemma mxdot_orthogonalmxr m n (P : 'M[R]_n) (A B : 'M[R]_(m, n)) : P \is orthogonalmx -> mxdot (A *m P) (B *m P) = mxdot A B.
Used by 11 declarations in 9 files
- this file: frobenius_orthogonalmxr
- GaussianAnalysis.matrix.real_spectral: spectral_mxdot
- GaussianAnalysis.matrix.psd_part: psd_nearest, psd_part_moreau, mxdot_psd_part_shift
- GaussianAnalysis.matrix.effective_rank: effective_rank_spec
- GaussianAnalysis.matrix.trace_projection: mxdot_conjmx
- GaussianAnalysis.probability.hanson_wright: gauss_chaos_mgf
- GaussianAnalysis.random_matrix.goe_rotation: goe_diag_var_tail
- GaussianAnalysis.comparison.brascamp_lieb: gauss_ibp_unit
- GaussianAnalysis.convex.gauss_feature: gauss_quad_moments
Arguments orthogonalmx {R n}.
Variable R : rcfType. Implicit Types m n : nat.
forall [R : rcfType] [m n : nat] [P : 'M_m] (A : 'M_(m, n)), P \is orthogonalmx -> frobenius (P *m A) = frobenius A
Statement as written in the source
Lemma frobenius_orthogonalmxl m n (P : 'M[R]_m) (A : 'M[R]_(m, n)) : P \is orthogonalmx -> frobenius (P *m A) = frobenius A.
Used by 2 declarations in 1 file
- GaussianAnalysis.matrix.opnorm: opnorm_orthogonalmxl, opnorm_orthogonalmxr
forall [R : rcfType] [m n : nat] [P : 'M_n] (A : 'M_(m, n)), P \is orthogonalmx -> frobenius (A *m P) = frobenius A
Stated in the README together with orthogonalmx.
Statement as written in the source
Lemma frobenius_orthogonalmxr m n (P : 'M[R]_n) (A : 'M[R]_(m, n)) : P \is orthogonalmx -> frobenius (A *m P) = frobenius A.
Used by 1 declaration in 1 file
- GaussianAnalysis.matrix.whitening: frobenius_whitening_mx