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github | noureldien/RecommenderSystem-master | tfocs_SCD.m | .m | RecommenderSystem-master/TFOCS/tfocs_SCD.m | 7,116 | utf_8 | bbb464c402a9d1aef7b095088dff964a | function [ x, odata, opts ] = tfocs_SCD( objectiveF, affineF, dualproxF, mu, x0, z0, opts, contOpts )
% TFOCS_SCD Smoothed conic dual form of TFOCS, for problems with non-trivial linear operators.
% [ x, out, opts ] = tfocs_SCD( objectiveF, affineF, dualproxF, mu, x0, z0, opts )
% Solves a conic problem using the smo... |
github | noureldien/RecommenderSystem-master | proj_0.m | .m | RecommenderSystem-master/TFOCS/proj_0.m | 1,651 | utf_8 | eca2879f7e76a6cc5846458df2840df7 | function op = proj_0(offset)
%PROJ_0 Projection onto the set {0}
% OP = PROJ_0 returns an implementation of the indicator
% function for the set including only zero.
%
% OP = PROJ_0( c ) returns an implementation of the
% indicator function of the set {c}
% If c is a scalar, this is interpreted as ... |
github | noureldien/RecommenderSystem-master | smooth_huber.m | .m | RecommenderSystem-master/TFOCS/smooth_huber.m | 1,503 | utf_8 | 7458a51d8c659b43327e5676daddfbd8 | function op = smooth_huber(tau )
%SMOOTH_HUBER Huber function generation.
% FUNC = SMOOTH_QUAD( TAU ) returns a function handle that implements
%
% FUNC(X) = 0.5 *( x.^2 )/tau if |x| <= tau
% = |x| - tau/2 if |x| > tau
%
% All arguments are optional; the d... |
github | noureldien/RecommenderSystem-master | tfunc_scale.m | .m | RecommenderSystem-master/TFOCS/tfunc_scale.m | 2,925 | utf_8 | 7657577392c3048b6ce5600899779bab | function op = tfunc_scale( funcF, s, A, b )
%TFUNC_SCALE Scaling a function.
% SSCALE = TFUNC_SCALE( FUNC, s, A, b ) is the function
% SSCALE( y ) = s * FUNC( A * y + b ).
% s must be a real scalar; A can be a scalar, a matrix, or a linear
% operator; and offset must be a vector of compatible size. The... |
github | noureldien/RecommenderSystem-master | solver_sDantzig_W.m | .m | RecommenderSystem-master/TFOCS/solver_sDantzig_W.m | 3,742 | utf_8 | cd27a69ba1228828c4351a5f57512626 | function varargout = solver_sDantzig_W( A,W, b, delta, mu, x0, z0, opts, varargin )
% SOLVER_SDANTZIG_W Weighted Dantzig selector problem. Uses smoothing.
%[ x, out, opts ] = solver_sDantzig_W( A,W, b, delta, mu, x0, z0, opts )
% Solves the smoothed Dantzig
% minimize norm(W*x,1) + (1/2)*mu*norm(x-x0).^2
% ... |
github | noureldien/RecommenderSystem-master | smooth_logsumexp.m | .m | RecommenderSystem-master/TFOCS/smooth_logsumexp.m | 1,241 | utf_8 | d1d17c729ec65be86dc59f23216be92f | function op = smooth_logsumexp(sigma)
% SMOOTH_LOGSUMEXP The function log(sum(exp(x)))
% returns a smooth function to calculate
% log( sum( exp(x) ) )
%
% SMOOTH_LOGSUMEXP( SIGMA ) is a scaled version
% that calclates sigma*log(sum(exp(x/sigma)), for sigma > 0.
% As sigma --> 0, this becomes a good approximatio... |
github | noureldien/RecommenderSystem-master | proj_singleAffine.m | .m | RecommenderSystem-master/TFOCS/proj_singleAffine.m | 1,700 | utf_8 | b074c8242355c9a250d8fa0562c0dbab | function op = proj_singleAffine( a, beta, ineq )
%PROJ_SINGLEAFFINE(a,beta) Projection onto the affine set { x : a'*x == beta }
% The parameter a may be a vector or matrix
% of the same size as x. By default, beta is 0
%PROJ_SINGLEAFFINE(a,beta,ineq)
% Projection onto the affine set { x : a'*x >= beta }
% ... |
github | noureldien/RecommenderSystem-master | proj_simplex.m | .m | RecommenderSystem-master/TFOCS/proj_simplex.m | 2,268 | utf_8 | 2609b69f26273903ad0ccfe6f288a1b3 | function op = proj_simplex( q )
%PROJ_SIMPLEX Projection onto the simplex.
% OP = PROJ_SIMPLEX( Q ) returns an nonsmooth function that
% represents the scaled simplex { x | x >= 0, sum(x) <= q }.
% Q is optional; if not supplied, it defaults to 1. If it is
% supplied, it must be a real positive scalar.
%
... |
github | noureldien/RecommenderSystem-master | smooth_logdet.m | .m | RecommenderSystem-master/TFOCS/smooth_logdet.m | 4,374 | utf_8 | 387fcdf0e739e8a02c1cdedb5e50386e | function op = smooth_logdet(q,C)
% SMOOTH_LOGDET The -log( det( X ) ) function.
% (Note the minus sign)
% FUNC = SMOOTH_LOGDET( q ) returns a function handle that
% provides a TFOCS-compatible implementation of the funciton
% -q*log( det( X ) )
%
% FUNC = SMOOTH_LOGDET( q, C ) represents
% -q*log(... |
github | noureldien/RecommenderSystem-master | proj_psdUTrace.m | .m | RecommenderSystem-master/TFOCS/proj_psdUTrace.m | 5,551 | utf_8 | 36c506d158b2e8e2870488875c90574d | function op = proj_psdUTrace( q, LARGESCALE, force_real, maxK )
%PROJ_PSDUTRACE Projection onto the positive semidefinite cone with fixed trace.
% OP = PROJ_PSDUTRACE( q ) returns a function that implements the
% indicator for the cone of positive semidefinite (PSD) matrices with
% fixed trace: { X | min(eig(... |
github | noureldien/RecommenderSystem-master | proj_maxEig.m | .m | RecommenderSystem-master/TFOCS/proj_maxEig.m | 4,041 | utf_8 | b8f7884c82d4bae9ed2cb84fa1bca1e3 | function op = proj_maxEig( q, LARGESCALE )
%PROJ_MAXEIG Projection onto the set of matrices with max eigenvalue less than or equal to q
% OP = PROJ_MAXEIG( q ) returns a function that implements the
% indicator for matrices with spectral norm less than q.
% Q is optional; if omitted, Q=1 is assumed. But if Q ... |
github | noureldien/RecommenderSystem-master | proj_conic.m | .m | RecommenderSystem-master/TFOCS/proj_conic.m | 1,267 | utf_8 | aa158e7e2bdc846087f0a3f7ba9f2eb0 | function op = proj_conic()
%PROJ_CONIC
% Returns an operator implementing projection onto
% the second order cone, aka (real) Lorentz cone
% aka ice-cream cone
% That is,
% { x : norm( x(1:end-1) , 2) <= x(end) }
%
% The cone is often written as
% { (x,t) : ||x|| <= t }
% so note that in this im... |
github | noureldien/RecommenderSystem-master | linop_matrix.m | .m | RecommenderSystem-master/TFOCS/linop_matrix.m | 3,073 | utf_8 | 3d4ba217f18cc74264746d9de3ad24ec | function op = linop_matrix( A, cmode, width )
%LINOP_MATRIX Linear operator, assembled from a matrix.
% If A is a real matrix, OP = LINOP_MATRIX( A ) returns a handle to a
% TFOCS linear operator that uses that matrix to implement its size,
% forward, and adjoint operations.
%
% If A is a complex matrix... |
github | noureldien/RecommenderSystem-master | prox_l2.m | .m | RecommenderSystem-master/TFOCS/prox_l2.m | 2,954 | utf_8 | fb75f3c83c7d686588db509d65f0b79e | function op = prox_l2( q )
%PROX_L2 L2 norm.
% OP = PROX_L2( q ) implements the nonsmooth function
% OP(X) = q * norm(X,'fro').
% Q is optional; if omitted, Q=1 is assumed. But if Q is supplied,
% then it must be a positive real scalar.
% If Q is a vector or matrix of the same size and dimensions... |
github | noureldien/RecommenderSystem-master | prox_max.m | .m | RecommenderSystem-master/TFOCS/prox_max.m | 1,835 | utf_8 | 2c780a81664b948ae167c14b9ee2c32a | function op = prox_max( q )
%PROX_MAX Entry-wise maximum element.
% OP = PROX_MAX( q ) implements the nonsmooth function
% OP(X) = q * max( X(:) ).
% Q is optional; if omitted, Q=1 is assumed. But if Q is supplied,
% then it must be a positive real scalar.
% Dual: proj_simplex.m (at least if X is a ... |
github | noureldien/RecommenderSystem-master | smooth_linear.m | .m | RecommenderSystem-master/TFOCS/smooth_linear.m | 1,246 | utf_8 | 2591511adff57675d9e7e39a1e77dc1d | function op = smooth_linear( c, d )
%SMOOTH_LINEAR Linear function generation.
% FUNC = SMOOTH_LINEAR( C, D ) returns a function handle that provides a
% TFOCS-compatible implementation of a linear function: if
% [F,G] = FUNC(X),
% then F = TFOCS_DOT(C,X)+D and G = C. D is optional; if omitted, then
% ... |
github | noureldien/RecommenderSystem-master | solver_psdComp.m | .m | RecommenderSystem-master/TFOCS/solver_psdComp.m | 2,258 | utf_8 | 0d03ebfdd9381a14620e19ffc84a64fc | function [ x, out, opts ] = solver_psdComp( Xinc, opts )
% SOLVER_PSDCOMP Matrix completion for PSD matrices.
% [ x, out, opts ] = solver_psdComp( Xinc, opts )
% Solves the PSD matrix completion problem
% minimize (1/2)*norm(X(ij)-vv).^2
% s.t. X p.s.d
% where ij is a vector of indices correspon... |
github | noureldien/RecommenderSystem-master | linop_scale.m | .m | RecommenderSystem-master/TFOCS/linop_scale.m | 1,961 | utf_8 | 7d1aed7f1e6ee832ec631e6d876c2ebb | function op = linop_scale( scale, sz )
%LINOP_SCALE Scaling linear operator.
% OP = LINOP_SCALE( scale ) returns a handle to a TFOCS linear operator
% whose forward and adjoint operators are OP(X) = scale * X.
% "scale" must be a real scalar
%
% OP = LINOP_SCALE( scale, size ) gives the scaling operator
... |
github | noureldien/RecommenderSystem-master | proj_linf.m | .m | RecommenderSystem-master/TFOCS/proj_linf.m | 1,095 | utf_8 | 3a679e695a32d386ea3b71f377ab271b | function op = proj_linf( q )
%PROJ_LINF Projection onto the scaled infinity norm ball.
% OP = PROJ_LINF( Q ) returns an operator implementing the
% indicator function for the infinity norm ball of size q,
% { X | norm( X, Inf ) <= q }. Q is optional; if omitted,
% Q=1 is assumed. But if Q is supplied, i... |
github | noureldien/RecommenderSystem-master | linop_TV.m | .m | RecommenderSystem-master/TFOCS/linop_TV.m | 6,508 | utf_8 | e32a5ac7f79b6395826bbfab8676536e | function op = linop_TV( sz, variation, action )
%LINOP_TV 2D Total-Variation (TV) linear operator.
% OP = LINOP_TV( SZ ) returns a handle to a TFOCS linear operator that
% implements the total variation linear operator on an M x N grid;
% that is, to be applied to matrices of size [M,N].
% By defau... |
github | noureldien/RecommenderSystem-master | linop_subsample.m | .m | RecommenderSystem-master/TFOCS/linop_subsample.m | 5,435 | utf_8 | c07783e03a8e5ffe3fdb3333f56582ff | function op = linop_subsample( sz, omega, SYMMETRIC )
%LINOP_SUBSAMPLE Subsampling linear operator.
%OP = LINOP_SUBSAMPLE( SZ, OMEGA )
% vector and matrix subsampling. Depending on SZ and OMEGA,
% this can do row-sampling (e.g. a partial FFT)
% or it can sample specific entries of a matrix (e.g. matrix completion... |
github | noureldien/RecommenderSystem-master | proj_box.m | .m | RecommenderSystem-master/TFOCS/proj_box.m | 1,334 | utf_8 | 4174575e366e60e84708c2af2ee90ea2 | function op = proj_box(l,u)
%PROJ_BOX Projection onto box constraints.
%PROJ_BOX(l,u) Projection onto the box { l <= x <= u }
% If l or u is the empty matrix [], then the constraint is not
% enforced (e.g. PROJ_BOX([],1) is the set { x <= 1 },
% and PROJ_BOX(0) is the set { 0 <= x } )
% The parameter... |
github | noureldien/RecommenderSystem-master | prox_l1linf.m | .m | RecommenderSystem-master/TFOCS/prox_l1linf.m | 2,840 | utf_8 | ca922a8fd4cbfffc75c6817c62cd4a53 | function op = prox_l1linf( q )
%PROX_L1LINF L1-LInf block norm: sum of L2 norms of rows.
% OP = PROX_L1LINF( q ) implements the nonsmooth function
% OP(X) = q * sum_{i=1:m} norm(X(i,:),Inf)
% where X is a m x n matrix. If n = 1, this is equivalent
% to PROX_L1
% Q is optional; if omitted, Q=1 is... |
github | noureldien/RecommenderSystem-master | linop_dot.m | .m | RecommenderSystem-master/TFOCS/linop_dot.m | 1,435 | utf_8 | ec2926ab13eaefd7c660d6b1eef2e9c3 | function op = linop_dot( A, adj )
%LINOP_DOT Linear operator formed from a dot product.
% OP = LINOP_DOT( A ) returns a handle to a TFOCS linear operator
% whose forward operation is OP(X) = TFOCS_DOT( A, X ).
% OP = LINOP_DOT( A, 1 ) returns the adjoint of that operator.
switch class( A ),
case 'double... |
github | noureldien/RecommenderSystem-master | prox_spectral.m | .m | RecommenderSystem-master/TFOCS/prox_spectral.m | 3,203 | utf_8 | 7d6095dccdfedfbfca0ff3d6327721e9 | function op = prox_spectral( q, SYM_FLAG )
%PROX_SPECTRAL Spectral norm, i.e. max singular value.
% OP = PROX_SPECTRAL( q ) implements the nonsmooth function
% OP(X) = q * max(svd(X)).
% Q is optional; if omitted, Q=1 is assumed. But if Q is supplied,
% it must be a positive real scalar.
%
% OP =... |
github | noureldien/RecommenderSystem-master | proj_l2.m | .m | RecommenderSystem-master/TFOCS/proj_l2.m | 2,606 | utf_8 | 01c909f42bdac5d071a7d3241b28d9b8 | function op = proj_l2( q )
%PROJ_L2 Projection onto the scaled 2-norm ball.
% OP = PROJ_L2( Q ) returns an operator implementing the
% indicator function for the 2-norm ball of size q,
% { X | norm( X, 2 ) <= q }. Q is optional; if omitted,
% Q=1 is assumed. But if Q is supplied, it must be a positive
%... |
github | noureldien/RecommenderSystem-master | proj_l2group.m | .m | RecommenderSystem-master/TFOCS/proj_l2group.m | 2,292 | utf_8 | 4d669ac6ad47eabfdbe3210105541c7c | function op = proj_l2group( q,group_indices )
%PROJ_L2GROUP Projection onto the intersection of scaled 2-norm balls.
% OP = PROJ_L2GROUP( Q, GROUP_INDICES ) returns an operator implementing the
% indicator function for the intersection of 2-norm ball of size q_k,
% i.e. intersection_k B_k
% where B_k = {... |
github | noureldien/RecommenderSystem-master | linop_vec.m | .m | RecommenderSystem-master/TFOCS/linop_vec.m | 1,411 | utf_8 | e51e7873b63106fa70d115b4947c1e16 | function op = linop_vec( sz )
%LINOP_VEC Matrix to vector reshape operator
%OP = LINOP_VEC( SZ )
% Constructs a TFOCS-compatible linear operator that reduces a matrix
% variable to a vector version using column-major order.
% This is equivalent to X(:)
% The transpose operator will reshape a vector into a m... |
github | noureldien/RecommenderSystem-master | proj_psd.m | .m | RecommenderSystem-master/TFOCS/proj_psd.m | 3,700 | utf_8 | cddfa5a145e99eb9f8c331a5ea845b62 | function op = proj_psd( LARGESCALE, isReal, K )
% PROJ_PSD Projection onto the positive semidefinite cone.
% OP = PROJ_PSD() returns a function that implements
% the projection onto the semidefinite cone:
% X = argmin_{min(eig(X))>=0} norm(X-Y,'fro')
%
% OP = PROJ_PSD( LARGESCALE )
% performs the same compu... |
github | noureldien/RecommenderSystem-master | proj_affine.m | .m | RecommenderSystem-master/TFOCS/proj_affine.m | 2,648 | utf_8 | a1ed4c92b72bed824e8a9869d9b9959f | function op = proj_affine( A, b, R )
%PROJ_AFFINE(A, b) Projection onto the affine set
% { x : A*x == b }
%
% Warning! For large dimensions, this may be costly.
% In this case, use proj_0 and explicitly seprate
% out the affine term (this is the motivation behind
% TFOCS).
%
% For efficiency, this fun... |
github | noureldien/RecommenderSystem-master | prox_Sl1.m | .m | RecommenderSystem-master/TFOCS/prox_Sl1.m | 2,766 | ibm852 | 40d9c28db6885fd0b32d5a65dcfef518 | function op = prox_Sl1( lambda )
%PROX_SL1 Sorted/Ordered L1 norm.
% OP = PROX_L1( lambda ) implements the nonsmooth function
% OP(X) = sum(lambda.*sort(abs(X),'descend'))
% where lambda is strictly positive and sorted in decreasing order,
% in which case this function is a norm (and hence convex).
%... |
github | noureldien/RecommenderSystem-master | prox_trace.m | .m | RecommenderSystem-master/TFOCS/prox_trace.m | 3,930 | utf_8 | fb718872754a7eab7a871a8a29f72a75 | function op = prox_trace( q, LARGESCALE, isReal )
%PROX_TRACE Nuclear norm, for positive semidefinite matrices. Equivalent to trace.
% OP = PROX_TRACE( q ) implements the nonsmooth function
% OP(X) = q * sum(svd(X)) = q*tr(X) ( X >= 0 assumed )
% Q is optional; if omitted, Q=1 is assumed. But if Q is ... |
github | noureldien/RecommenderSystem-master | linop_reshape.m | .m | RecommenderSystem-master/TFOCS/linop_reshape.m | 1,353 | utf_8 | a6f1e49bd4eeb1346e6587eed03de5c4 | function op = linop_reshape( sz_in, sz_out )
%LINOP_RESHAPE Linear operator to perform reshaping of matrices.
% op = linop_reshape( sz_in, sz_out ) creates a linear operator that
% uses the matlab 'reshape' function to reshape between sz_in and sz_out.
% Both sz_in and sz_out must be vectors with d elem... |
github | noureldien/RecommenderSystem-master | linop_spot.m | .m | RecommenderSystem-master/TFOCS/linop_spot.m | 2,641 | utf_8 | 165fe5006092b91cf939a33d3e59360d | function op = linop_spot( A, cmode )
%LINOP_SPOT Linear operator, assembled from a SPOT operator.
% If A is a real operator, OP = LINOP_SPOT( A ) returns a handle to a
% TFOCS linear operator that uses that object to implement its size,
% forward, and adjoint operations.
%
% If A is a complex operator, ... |
github | noureldien/RecommenderSystem-master | smooth_quad.m | .m | RecommenderSystem-master/TFOCS/smooth_quad.m | 5,249 | utf_8 | 744d42579d5cf2ce8e77d0bc10190371 | function op = smooth_quad( P, q, r, use_eig )
%SMOOTH_QUAD Quadratic function generation.
% FUNC = SMOOTH_QUAD( P, q, r ) returns a function handle that implements
%
% FUNC(X) = 0.5 * TFOCS_DOT( P * x, x ) + TFOCS_DOT( q, x ) + r.
%
% All arguments are optional; the default values are P=I, q=0, r=0. In
% ... |
github | noureldien/RecommenderSystem-master | solver_sNuclearBPDN.m | .m | RecommenderSystem-master/TFOCS/solver_sNuclearBPDN.m | 3,011 | utf_8 | 29336466c9067d1573e150cfb481c52d | function varargout = solver_sNuclearBPDN( omega, b, epsilon, mu, x0, z0, opts, varargin )
% SOLVER_SNUCLEARBPDN Nuclear norm basis pursuit problem with relaxed constraints. Uses smoothing.
% [ x, out, opts ] = solver_sNuclearBPDN( omega, b, epsilon,mu, X0, Z0, opts )
% Solves the smoothed nuclear norm basis pursuit ... |
github | noureldien/RecommenderSystem-master | smooth_logLPoisson.m | .m | RecommenderSystem-master/TFOCS/smooth_logLPoisson.m | 1,374 | utf_8 | 7a38ab995f3178c5a4eead5a05e18657 | function op = smooth_logLPoisson(x)
% SMOOTH_LOGLPOISSON Log-likelihood of a Poisson: sum_i (-lambda_i + x_i * log( lambda_i) )
% OP = SMOOTH_LOGLPOISSON( X )
% returns a function that computes the log-likelihood function
% of independent Poisson random variables with parameters lambda_i:
%
% log-likelihood... |
github | noureldien/RecommenderSystem-master | prox_hingeDual.m | .m | RecommenderSystem-master/TFOCS/prox_hingeDual.m | 2,826 | utf_8 | c9ee19474738fbfc039664c567465e9e | function op = prox_hingeDual( q , r, y)
%PROX_HINGEDUAL Dual function of the Hinge-loss function.
% OP = PROX_HINGEDUAL( q , r , y) implements the nonsmooth function
% that is dual to the Hinge-loss function f, where
% f(x) = q * sum( max( r - y.*x, 0 ) ).
% Q is optional; if omitted, Q=1 is as... |
github | noureldien/RecommenderSystem-master | prox_hinge.m | .m | RecommenderSystem-master/TFOCS/prox_hinge.m | 2,241 | utf_8 | 572665f0bfcd52f510affa19e5834422 | function op = prox_hinge( q , r, y)
%PROX_HINGE Hinge-loss function.
% OP = PROX_HINGE( q , r, y ) implements the nonsmooth function
% OP(X) = q * sum( max( r - y.*x, 0 ) ).
% Q is optional; if omitted, Q=1 is assumed. But if Q is supplied,
% then it must be a positive real scalar.
% R is also op... |
github | noureldien/RecommenderSystem-master | smooth_handles.m | .m | RecommenderSystem-master/TFOCS/smooth_handles.m | 846 | utf_8 | 8c8059e8cf9ca09325f64157596796f0 | function op = smooth_handles( func, grad )
%SMOOTH_HANDLES Smooth function from separate f/g handles.
% OP = SMOOTH_HANDLES( func, grad ) constructs a TFOCS-compatible
% smooth function from separate handles for computing the function
% value and gradient.
%
% See also private/tfocs_smooth
op = @(varargin)... |
github | noureldien/RecommenderSystem-master | smooth_constant.m | .m | RecommenderSystem-master/TFOCS/smooth_constant.m | 944 | utf_8 | 5993f975dd9dc6fbff21c31ad037da68 | function op = smooth_constant( d )
%SMOOTH_CONSTANT Constant function generation.
% FUNC = SMOOTH_CONSTANT( D ) returns a function handle that provides
% a TFOCS-compatible implementation of the constant function F(X) = D.
% D must be a real scalar. The function can be used in both a smooth
% and a nonsmooth... |
github | noureldien/RecommenderSystem-master | prox_boxDual.m | .m | RecommenderSystem-master/TFOCS/prox_boxDual.m | 2,537 | utf_8 | 4e9b22ef42295ecd62b77531410c8190 | function op = prox_boxDual(l,u,scale)
%PROX_BOXDUAL Dual function of box indicator function { l <= x <= u }
%PROX_BOXDUAL(l,u) Dual function of box indicator function { l <= x <= u }
% If l or u is the empty matrix [], then the constraint is not
% enforced (e.g. PROJ_BOXDUAL([],1) is the set { x <= 1 },
% ... |
github | noureldien/RecommenderSystem-master | prox_linf.m | .m | RecommenderSystem-master/TFOCS/prox_linf.m | 1,272 | utf_8 | d8c9a16d106bba24ebed9be8d5b2e009 | function op = prox_linf( q )
%PROX_LINF L-infinity norm.
% OP = PROX_LINF( q ) implements the nonsmooth function
% OP(X) = q * norm( X(:), Inf ).
% Q is optional; if omitted, Q=1 is assumed. But if Q is supplied,
% then it must be a positive real scalar.
% Dual: proj_l1.m
% See also proj_l1
if narg... |
github | noureldien/RecommenderSystem-master | prox_scale.m | .m | RecommenderSystem-master/TFOCS/prox_scale.m | 2,292 | utf_8 | 5810ae35dfb34e2bb4ca36f8cee31668 | function op = prox_scale( proxF, scale )
%PROX_SCALE Scaling a proximity/projection function.
% PSCALE = PROX_SCALE( PROXF, s ) is the proximity function formed
% by multiplying the input by the real value SCALE, then calling the
% function PROXF. In other words,
% PSCALE( y ) = PROXF( s * y ).
% ... |
github | noureldien/RecommenderSystem-master | linop_TV3D.m | .m | RecommenderSystem-master/TFOCS/linop_TV3D.m | 6,774 | utf_8 | cc42bad79344ce0058bbb44a9a23b805 | function op = linop_TV3D( sz, variation, action )
%LINOP_TV3D 3D Total-Variation (TV) linear operator.
% OP = LINOP_TV3D( SZ ) returns a handle to a TFOCS linear operator that
% implements the total variation linear operator on an M x N x P grid;
% that is, to be applied to volume stacks of size [M... |
github | noureldien/RecommenderSystem-master | prox_dualize.m | .m | RecommenderSystem-master/TFOCS/prox_dualize.m | 3,560 | utf_8 | aa0b00f290b1ad5e0ddc4bd0625fb7f2 | function op = prox_dualize( dualProx, NEG )
%PROX_DUALIZE Define a proximity function by its dual
% OP = PROX_DUALIZE( dualOp ) returns an operator implementing the
% dual of the function dualProx. You can verify they are duals
% via test_proxPair( dualOp, OP ).
%
% OP = PROX_DUALIZE( dualOp, 'neg' )
% ... |
github | noureldien/RecommenderSystem-master | proj_l1.m | .m | RecommenderSystem-master/TFOCS/proj_l1.m | 1,424 | utf_8 | c320de15ae7a8dc29d99628aad575818 | function op = proj_l1( q )
%PROJ_L1 Projection onto the scaled 1-norm ball.
% OP = PROJ_L1( Q ) returns an operator implementing the
% indicator function for the 1-norm ball of radius q,
% { X | norm( X, 1 ) <= q }. Q is optional; if omitted,
% Q=1 is assumed. But if Q is supplied, it must be a positive
... |
github | noureldien/RecommenderSystem-master | linop_handles.m | .m | RecommenderSystem-master/TFOCS/linop_handles.m | 3,293 | utf_8 | 6c782762ef1c75e5f56065543f3a4580 | function op = linop_handles( sz, Af, At, cmode )
%LINOP_HANDLES Linear operator from user-supplied function handles.
%OP = LINOP_HANDLES( SZ, AF, AT, CMODE )
% Constructs a TFOCS-compatible linear operator from separate function
% handles that compute the forward and adjoint operations. The first
% argument, S... |
github | noureldien/RecommenderSystem-master | linop_fft.m | .m | RecommenderSystem-master/TFOCS/linop_fft.m | 6,749 | utf_8 | 49193b472db7ac33d779b95d586faea1 | function op = linop_fft( N, bigN, cmode, width )
%LINOP_FFT Fast Fourier transform linear operator.
% OP = LINOP_FFT( N )
% returns a function handle that computes the 1D FFT.
% If given a matrix, it operates on each column separately (i.e. it
% does NOT automatically switch to a 2D FFT).
%
% By default, it ass... |
github | noureldien/RecommenderSystem-master | smooth_logLLogistic.m | .m | RecommenderSystem-master/TFOCS/smooth_logLLogistic.m | 1,377 | utf_8 | d6f15dda14892f596464c6df19b9e884 | function op = smooth_logLLogistic(y)
% SMOOTH_LOGLLOGISTIC Log-likelihood function of a logistic: sum_i( y_i mu_i - log( 1+exp(mu_i) ) )
% OP = SMOOTH_LOGLLOGISTIC( Y )
% returns a function that computes the log-likelihood function
% in a standard logistic regression model with independent entries. There
% are ... |
github | noureldien/RecommenderSystem-master | tfunc_sum.m | .m | RecommenderSystem-master/TFOCS/tfunc_sum.m | 1,411 | utf_8 | e4b7d9e16c4c2aa069ece8af245f1096 | function op = tfunc_sum( varargin )
%TFUNC_SUM Sum of functions.
% OP = TFUNC_SUM( F1, F2, ..., FN ) implements
% OP( x ) = F1( x ) + F2( x ) + ... + FN( x ).
% Each entry must be a real scalar or a function handle. You are
% responsible for ensuring that the sum is convex or concave, as
% appropria... |
github | noureldien/RecommenderSystem-master | linop_compose.m | .m | RecommenderSystem-master/TFOCS/linop_compose.m | 2,562 | utf_8 | cb490a940713eb0720d36f72186db7df | function op = linop_compose( varargin )
%LINOP_COMPOSE Composes two TFOCS linear operators
%OP = LINOP_COMPOSE( OP1, OP2, ..., OPN )
% Constructs a TFOCS-compatible linear operator from the composition of
% two or more linear operators and/or matrices. That is,
% OP(x,1) = OP1(OP2(...(OPN(x,1),...,1),1)
% ... |
github | noureldien/RecommenderSystem-master | smooth_entropy.m | .m | RecommenderSystem-master/TFOCS/smooth_entropy.m | 571 | utf_8 | eafb7ce5621bcaafc8716fad98a6317e | function op = smooth_entropy()
%SMOOTH_ENTROPY The entropy function -sum( x_i log(x_i) )
op = @smooth_entropy_impl;
function [ v, g ] = smooth_entropy_impl( x )
if any( x < 0 ),
v = -Inf;
if nargout > 1,
g = NaN * ones(size(x));
end
else
logx = log(max(x,realmin));
v = - tfocs_dot( x, logx ... |
github | noureldien/RecommenderSystem-master | proj_linfl2.m | .m | RecommenderSystem-master/TFOCS/proj_linfl2.m | 1,896 | utf_8 | 0a7b818f354d63c32ae307163ee9db91 | function op = proj_linfl2( q )
%PROJ_LINFL2 Projection of each row onto the scaled l2 norm ball.
% OP = PROJ_LINFL2( Q ) returns an operator implementing the
% indicator function for the set of l2 norm ball of size q,
% { X | for all rows i, norm( X(i,:),2) <= q }. Q is optional; if omitted,
% Q=1 is as... |
github | noureldien/RecommenderSystem-master | proj_boxAffine.m | .m | RecommenderSystem-master/TFOCS/proj_boxAffine.m | 4,399 | utf_8 | daabfe60888cdc7be71d4038bc6fd2ec | function op = proj_boxAffine( a, l, u, alpha )
%PROJ_BOXAFFINE(a,l,u,alpha) Projection onto the box { l <= x <= u } intersected
% with the constraint a'*x == alpha
% If l or u is the empty matrix [], then the constraint is not
% enforced. "a" must be included (otherwise, use proj_box.m).
% The parameters... |
github | noureldien/RecommenderSystem-master | continuation.m | .m | RecommenderSystem-master/TFOCS/continuation.m | 9,214 | utf_8 | f32c7022dc11868602b1aa19f1327085 | function [ x, odata, optsOut ] = continuation( fcn, mu, x0, z0, opts, contOpts )
% CONTINUATION Meta-wrapper to run TFOCS_SCD in continuation mode.
% [...] = CONTINUATION( FCN, MU, X0, Z0, OPTS, CONT_OPTS )
% is a wrapper to perform continuation on FCN, where
% FCN is a function that calls tfocs_SCD or a tfocs solv... |
github | noureldien/RecommenderSystem-master | linop_test.m | .m | RecommenderSystem-master/TFOCS/linop_test.m | 6,675 | utf_8 | f70ad1b3ce64c1562b930a7b2a16a719 | function varargout = linop_test( op, cmode, maxits )
%LINOP_TEST Performs an adjoint test on a linear operator.
% LINOP_TEST( OP ) attempts to verify that a linear operator OP obeys
% the inner product test: <A*x,y> = <x,A'*y> for all x, y. OP must be a
% TFOCS linear operator with hard-coded size information... |
github | noureldien/RecommenderSystem-master | prox_l1l2.m | .m | RecommenderSystem-master/TFOCS/prox_l1l2.m | 1,965 | utf_8 | d0c5913c57cd5565c381d72630e49577 | function op = prox_l1l2( q )
%PROX_L1L2 L1-L2 block norm: sum of L2 norms of rows.
% OP = PROX_L1L2( q ) implements the nonsmooth function
% OP(X) = q * sum_{i=1:m} norm(X(i,:),2)
% where X is a m x n matrix. If n = 1, this is equivalent
% to PROX_L1
% Q is optional; if omitted, Q=1 is assumed. ... |
github | noureldien/RecommenderSystem-master | solver_sNuclearBP.m | .m | RecommenderSystem-master/TFOCS/solver_sNuclearBP.m | 3,758 | utf_8 | e3f2d765c361ba26556f619b1e68b49c | function varargout = solver_sNuclearBP( omega, b, mu, x0, z0, opts, varargin )
% SOLVER_SNUCLEARBP Nuclear norm basis pursuit problem (i.e. matrix completion). Uses smoothing.
% [ x, out, opts ] = solver_sNuclearBP( omega, b, mu, X0, Z0, opts )
% Solves the smoothed nuclear norm basis pursuit problem
% minimi... |
github | noureldien/RecommenderSystem-master | makeMex.m | .m | RecommenderSystem-master/TFOCS/mexFiles/makeMex.m | 1,454 | utf_8 | 3b64a02ebae63926380e6905e4b15c43 | function makeMex()
% Script to install mex files
% Change directory, so all mex files are in the mexFiles/ subdirectory
here = pwd;
cd( fullfile(tfocs_where,'mexFiles') );
if exist('OCTAVE_VERSION','builtin')
octave = true;
compileFunction = @compileForOctave;
else
octave = false;
compileFunction = @c... |
github | noureldien/RecommenderSystem-master | project2DCone.m | .m | RecommenderSystem-master/TFOCS/examples/demos/project2DCone.m | 1,867 | utf_8 | 026625522ad5af5ffefab657f635b1b4 | function op = project2DCone(x1, x2 )
% OP = project2DCone( y, x1, x2 )
% represents the 2D point cone defined
% by the vectors x1 and x2. x1 should be "left" of x2,
% and the cone is defined as the region to the right
% of x1 and to the left of x2.
error(nargchk(1,2,nargin));
if nargin < 2, u = []; end
%op = @... |
github | noureldien/RecommenderSystem-master | test_quadratic_constrained.m | .m | RecommenderSystem-master/TFOCS/examples/smallscale/test_quadratic_constrained.m | 2,065 | utf_8 | e0af4d6b9d96d12962ba86e872d6b248 | function test_quadratic_constrained
%% Tests the solvers on a simple constrained quadratic function
%{
Solve:
minimize_x c'x + x'Dx/2
subject to ||x||_1 <= 10
as an example of using TFOCS without the "SCD" interface
(since the objective is smooth and we can project, there's
no need to smoo... |
github | noureldien/RecommenderSystem-master | PsiWFF.m | .m | RecommenderSystem-master/TFOCS/examples/largescale/PsiWFF.m | 2,210 | utf_8 | 0a8a657f2aad6c0c3586181a57daa34d | function x = PsiWFF(y,w_type,log_length,min_scale,max_scale,shift_redundancy,freq_redundancy);
% Windowed Fourier Frame Synthesis
% x = PsiWFF(y,w_type,log_length,min_scale,max_scale,shift_redundancy,freq_redundancy);
% w_type is the type of window. Currently, this supports 'isine' (iterate sine)
% and 'gaussian'.... |
github | noureldien/RecommenderSystem-master | PsiTransposeWFF.m | .m | RecommenderSystem-master/TFOCS/examples/largescale/PsiTransposeWFF.m | 2,291 | utf_8 | 0c4c219b69706f2eb3079624bc942c7e | function y = PsiTransposeWFF(x,w_type,log_length,min_scale,max_scale,shift_redundancy,freq_redundancy, PLOT)
% Windowed Fourier Frame Analysis
% y = PsiTransposeWFF( x, w_type, log_length, min_scale, max_scale,...
% shift_redundancy, freq_redundancy, plot )
% w_type is the type of window. Currently, this suppo... |
github | noureldien/RecommenderSystem-master | prox_stack.m | .m | RecommenderSystem-master/TFOCS/private/prox_stack.m | 1,573 | utf_8 | 6abdefa775dc0247da59d5f9da328de6 | function op = prox_stack( varargin )
% OP = PROJ_STACK( P1, P2, P3, ..., PN )
% "Stacks" N proximity functions P1, P2, P3, ..., PN together, to create
% a single proximity function that operates on an N-tuple. Returns a
% function handle ready to be used in
args = varargin;
while isa( args, 'cell' ) && nume... |
github | noureldien/RecommenderSystem-master | linop_stack.m | .m | RecommenderSystem-master/TFOCS/private/linop_stack.m | 9,818 | utf_8 | 362a65defc9647b6018de3f8bb84f008 | function [ op, inp_dims, otp_dims ] = linop_stack( linearF, inp_dims, otp_dims, DO_DEBUG )
%LINOP_STACK Stacked linear operators.
% OP = LINOP_STACK( linearF ), where linearF is a cell vector or cell
% matrix, returns a function handle for a linear operator that accepts
% TFOCS_TUPLE objects as input or ou... |
github | noureldien/RecommenderSystem-master | size_compat.m | .m | RecommenderSystem-master/TFOCS/private/size_compat.m | 1,926 | utf_8 | 4f7ac6aa67517bee0c7c6b9e8f5cb47a | function [ a, sX ] = size_compat( sX, sY )
a = true;
switch class( sX ),
case 'double',
if isempty( sX ) || all( sX == 0 ),
sX = sY;
elseif isempty( sY ) || all( sY == 0 ),
elseif ~isequal( sX, sY ),
% Feb 29, 2012. Special case:
% One repre... |
github | noureldien/RecommenderSystem-master | smooth_stack.m | .m | RecommenderSystem-master/TFOCS/private/smooth_stack.m | 1,162 | utf_8 | 72e46053bc55cd4cdb03ddd2ca127922 | function op = smooth_stack( varargin )
% OP = SMOOTH_STACK( S1, S2, S3, ..., SN )
% "Stacks" N smooth functions S1, S2, S3, ..., SN together to create
% a single smooth function that operates on an N-tuple. Returns a
% function handle ready to be used in TFOCS.
args = varargin;
while isa( args, 'cell' ) && n... |
github | noureldien/RecommenderSystem-master | tfocs_zeros.m | .m | RecommenderSystem-master/TFOCS/private/tfocs_zeros.m | 1,952 | utf_8 | b6821ebb7e91840469b780e1a8d004eb | function z = tfocs_zeros( y )
switch class( y ),
case 'double',
% SRB: this was the old code. This function was intended
% to be called as tfocs_zeros( size(y) )
% But, for packSVD, I'd prefer to call it as tfocs_zeros(y)
% so that we can look at the type of y and pass it off
... |
github | noureldien/RecommenderSystem-master | tfocs_prox.m | .m | RecommenderSystem-master/TFOCS/private/tfocs_prox.m | 3,563 | utf_8 | e729a37f91473c7a21710186efd642e4 | function op = tfocs_prox( f, prox_f, VECTOR_SCALAR )
% OP = TFOCS_PROX( F, PROX_F )
% combines F and PROX_F into the appropriate TFOCS-compatible object.
%
% F is any function (with known proximity operator),
% and PROX_F is its proximity operator, defined as:
%
% PROX_F( Y, t ) = argmin_X F(X) + 1/(2*t)*|| X ... |
github | noureldien/RecommenderSystem-master | tfocs_smooth.m | .m | RecommenderSystem-master/TFOCS/private/tfocs_smooth.m | 1,201 | utf_8 | 82b5b7f371affdcd659912559e5ac67b | function op = tfocs_smooth( fcn )
% OP = TFOCS_SMOOTH(FCN)
% is a wrapper designed to facilitate users writing their own
% smooth functions.
%
% To use this, please see the file SMOOTH_HUBER as an example
%
% The basic layout of a file like SMOOTH_HUBER is as follows:
%
% function op = smooth_huber(mu)
% ... |
github | noureldien/RecommenderSystem-master | byteSize.m | .m | RecommenderSystem-master/Shared/byteSize.m | 975 | utf_8 | 650a543ac04654ac281f5595607e0601 | function byteSize(in, fid)
% BYTESIZE writes the memory usage of the provide variable to the given file
% identifier. Output is written to screen if fid is 1, empty or not provided.
if nargin == 1 || isempty(fid)
fid = 1;
end
s = whos('in');
fprintf(fid,[Bytes2str(s.bytes) '\n']);
end
function str = Bytes2str(Nu... |
github | noureldien/RecommenderSystem-master | lanbpro.m | .m | RecommenderSystem-master/SVT/lanbpro.m | 20,196 | utf_8 | a0f5dc1725c085270e15fedff60788bc | function [U,B_k,V,p,ierr,work] = lanbpro(varargin)
%LANBPRO Lanczos bidiagonalization with partial reorthogonalization.
% LANBPRO computes the Lanczos bidiagonalization of a real
% matrix using the with partial reorthogonalization.
%
% [U_k,B_k,V_k,R,ierr,work] = LANBPRO(A,K,R0,OPTIONS,U_old,B_old,V_old... |
github | noureldien/RecommenderSystem-master | cvx_version.m | .m | RecommenderSystem-master/cvx/cvx_version.m | 14,458 | utf_8 | 2d6b5dc232fa3eae5c5f570d43ae7fb4 | function varargout = cvx_version( varargin )
% CVX_VERSION Returns version and environment information for CVX.
%
% When called with no arguments, CVX_VERSION prints out version and
% platform information that is needed when submitting CVX bug reports.
%
% This function is also used internally to return use... |
github | noureldien/RecommenderSystem-master | cvx_grbgetkey.m | .m | RecommenderSystem-master/cvx/cvx_grbgetkey.m | 19,096 | utf_8 | 080162e4fd27b14ea8387362148db7d1 | function success = cvx_grbgetkey( kcode, overwrite )
% CVX_GRBGETKEY Retrieves and saves a Gurobi/CVX license.
%
% This function is used to install Gurobi license keys for use in CVX. It
% is called with your Gurobi license code as a string argument; e.g.
%
% cvx_grbgetkey xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
% ... |
github | noureldien/RecommenderSystem-master | HSDNTcorr.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDNTcorr.m | 1,001 | utf_8 | c42eba1c6bae660b88921b7c8747490e | %%************************************************************************
%% HSDNTcorr: corrector step for the NT direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%************************************************************************
f... |
github | noureldien/RecommenderSystem-master | HSDHKMdirfun.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDHKMdirfun.m | 1,551 | utf_8 | 1034e25e48a42d2fa143f93f47961fe9 | %%*******************************************************************
%% HSDHKMdirfun: compute (dX,dZ), given dy, for the HKM direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%****************************************************************... |
github | noureldien/RecommenderSystem-master | HSDsqlp.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDsqlp.m | 11,860 | utf_8 | 00b8311a8efbee36662ca9288870a1cd | %%*****************************************************************************
%% HSDsqlp: solve an semidefinite-quadratic-linear program
%% by infeasible path-following method on the homogeneous self-dual model.
%%
%% [obj,X,y,Z,info,runhist] =
%% HSDsqlp(blk,At,C,b,OPTIONS,X0,y0,Z0);
%%
%% Input: blk: a cel... |
github | noureldien/RecommenderSystem-master | HSDsortA.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDsortA.m | 2,577 | utf_8 | 0a74ddbb8a0c79bf22592d780d865e06 | %%*********************************************************************
%% sortA: sort columns of At{p} in ascending order according to the
%% number of nonzero elements.
%%
%% [At,C,b,X0,Z0,permA,permZ] = sortA(blk,At,C,b,X0,Z0);
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tut... |
github | noureldien/RecommenderSystem-master | HSDHKMrhsfun.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDHKMrhsfun.m | 2,666 | utf_8 | 16409ae4672f80ef54a33c31ef30000f | %%*******************************************************************
%% HSDHKMrhsfun: compute the right-hand side vector of the
%% Schur complement equation for the HKM direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%*****... |
github | noureldien/RecommenderSystem-master | HSDsqlpcheckconvg.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDsqlpcheckconvg.m | 6,249 | utf_8 | a579e4972fd77d5cc3e11b72bf56d3a9 | %%*****************************************************************************
%% HSDsqlpcheckconvg: check convergence.
%%
%% ZpATynorm, AX, normX, normZ are with respect to the
%% original variables, not the HSD variables.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last ... |
github | noureldien/RecommenderSystem-master | HSDNTdirfun.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDNTdirfun.m | 1,459 | utf_8 | a045827a3ca1adcf8806cfd8234ad5e4 | %%*******************************************************************
%% HSDNTdirfun: compute (dX,dZ), given dy, for the NT direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%******************************************************************... |
github | noureldien/RecommenderSystem-master | HSDNTrhsfun.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDNTrhsfun.m | 3,424 | utf_8 | 02348c55d691a53b023639b8103757be | %%*******************************************************************
%% HSDNTrhsfun: compute the right-hand side vector of the
%% Schur complement equation for the NT direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%*********... |
github | noureldien/RecommenderSystem-master | HSDHKMpred.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDHKMpred.m | 2,644 | utf_8 | 81b89c36e0d0bad30836c551264a6a05 | %%*******************************************************************
%% HSDHKMpred: Compute (dX,dy,dZ) for the H..K..M direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%*******************************************************************
f... |
github | noureldien/RecommenderSystem-master | HSDsqlpmain.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDsqlpmain.m | 28,293 | utf_8 | e3f6670b9b1de0ad08e099276bc20c35 | %%*****************************************************************************
%% HSDsqlp: solve an semidefinite-quadratic-linear program
%% by infeasible path-following method on the homogeneous self-dual model.
%%
%% [obj,X,y,Z,info,runhist] =
%% HSDsqlp(blk,At,C,b,OPTIONS,X0,y0,Z0,kap0,tau0,theta0);
%%
%% ... |
github | noureldien/RecommenderSystem-master | HSDlinsysolve.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDlinsysolve.m | 6,495 | utf_8 | 0644ae75443d221edcf585f5a5736fe5 | %%***************************************************************
%% linsysolve: solve linear system to get dy, and direction
%% corresponding to unrestricted variables.
%%
%% [xx,coeff,L,resnrm] = linsysolve(schur,UU,EE,Bmat,rhs);
%%
%% child functions: mybicgstable.m
%%
%% SDPT3: version 3.1
%% Copyright ... |
github | noureldien/RecommenderSystem-master | HSDsqlpmisc.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDsqlpmisc.m | 3,299 | utf_8 | f36316ddff8099a74241fa1590fc584a | %%*****************************************************************************
%% HSDsqlpmisc:
%% produce infeasibility certificates if appropriate
%%
%% Input: X,y,Z are the original variables, not the HSD variables.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modifi... |
github | noureldien/RecommenderSystem-master | HSDbicgstab.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDbicgstab.m | 3,084 | utf_8 | 96ee9f939e0b2527113539aa0b633ffc | %%*************************************************************************
%% HSDbicgstab
%%
%% [xx,resnrm,flag] = HSDbicgstab(A,b,M1,tol,maxit)
%%
%% iterate on bb - (M1)*AA*x
%%
%% r = b-A*xtrue;
%%
%%*************************************************************************
function [xx,resnrm,flag] = HSDbicgstab(... |
github | noureldien/RecommenderSystem-master | HSDHKMcorr.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDHKMcorr.m | 985 | utf_8 | 1e1983a66956f1d3e4e8e279b1dbe2d0 | %%*****************************************************************
%% HSDHKMcorr: corrector step for the HKM direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%*****************************************************************
function [par... |
github | noureldien/RecommenderSystem-master | HSDNTpred.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDNTpred.m | 2,034 | utf_8 | e194daf53d375b24154b1caf94b7646d | %%**********************************************************************
%% HSDNTpred: Compute (dX,dy,dZ) for NT direction.
%%
%% compute SVD of Xchol*Zchol via eigenvalue decompostion of
%% Zchol * X * Zchol' = V * diag(sv2) * V'.
%% compute W satisfying W*Z*W = X.
%% W = G'*G, where G = diag(sqrt(sv)) * (inv... |
github | noureldien/RecommenderSystem-master | HSDsqlpCpert.m | .m | RecommenderSystem-master/cvx/sdpt3/HSDSolver/HSDsqlpCpert.m | 2,263 | utf_8 | 326ec0065ebb155fab5ee8b4670ec0db | %%*****************************************************************************
%% HSDsqlpCpert: perturb C.
%%
%%*****************************************************************************
function [At,Cpert] = HSDsqlpCpert(blk,At,par,C,X,Cpert,runhist)
iter = length(runhist.pinfeas);
prim_infeas = runhist.pinfeas(... |
github | noureldien/RecommenderSystem-master | cheby0.m | .m | RecommenderSystem-master/cvx/sdpt3/Examples/cheby0.m | 2,576 | utf_8 | a31e95ee5e80694cd1c3f2ceb594d369 | %%**********************************************************
%% cheby0:
%%
%% minimize || p(d) ||_infty
%% p = polynomial of degree <= m such that p(0) = 1.
%%
%% Here d = n-vector
%%----------------------------------------------------------
%% [blk,Avec,C,b,X0,y0,Z0,objval,p] = cheby0(d,m,solve);
%%
%% d ... |
github | noureldien/RecommenderSystem-master | randmat.m | .m | RecommenderSystem-master/cvx/sdpt3/Solver/randmat.m | 811 | utf_8 | 483225eceeb882378d1a6fc61914a4be | %%******************************************************
%% randmat: generate an mxn matrix using matlab's
%% rand or randn functions using state = k.
%%
%%******************************************************
function v = randmat(m,n,k,randtype)
try
s = rng;
rng(k);
if strcmp(randtype,... |
github | noureldien/RecommenderSystem-master | skron.m | .m | RecommenderSystem-master/cvx/sdpt3/Solver/skron.m | 1,389 | utf_8 | 3aba6bed9dc50b45f766b4a8620c4ac3 | %%***********************************************************************
%% skron: Find the matrix presentation of
%% symmetric kronecker product skron(A,B), where
%% A,B are symmetric.
%%
%% Important: A,B are assumed to be symmetric.
%%
%% K = skron(blk,A,B);
%%
%% blk: a cell array specifying the b... |
github | noureldien/RecommenderSystem-master | NTcorr.m | .m | RecommenderSystem-master/cvx/sdpt3/Solver/NTcorr.m | 1,315 | utf_8 | 458c52ec6bf00d3507df137889a53c7e | %%************************************************************************
%% NTcorr: corrector step for the NT direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%************************************************************************
func... |
github | noureldien/RecommenderSystem-master | HKMcorr.m | .m | RecommenderSystem-master/cvx/sdpt3/Solver/HKMcorr.m | 1,313 | utf_8 | ff69a87fe927bf7f964fd55cbf7ec718 | %%*****************************************************************
%% HKMcorr: corrector step for the HKM direction.
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%*****************************************************************
function [dX,dy,... |
github | noureldien/RecommenderSystem-master | steplength.m | .m | RecommenderSystem-master/cvx/sdpt3/Solver/steplength.m | 5,590 | utf_8 | 2b52f7d5b9712cf17885f9ca3eaeb666 | %%***************************************************************************
%% steplength: compute xstep such that X + xstep*dX >= 0.
%%
%% [xstep] = steplength(blk,X,dX,Xchol,invXchol);
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%***********... |
github | noureldien/RecommenderSystem-master | SDPT3data_SEDUMIdata.m | .m | RecommenderSystem-master/cvx/sdpt3/Solver/SDPT3data_SEDUMIdata.m | 3,843 | utf_8 | 26106829dfa4c0fbb1ca8c4aa9839fa8 | %%**********************************************************
%% SDPT3data_SEDUMIdata: convert SQLP data in SDPT3 format to
%% SeDuMi format
%%
%% [At,b,c,K] = SDPT3data_SEDUMIdata(blk,AAt,CC,bb);
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modifie... |
github | noureldien/RecommenderSystem-master | schurmat_sblk.m | .m | RecommenderSystem-master/cvx/sdpt3/Solver/schurmat_sblk.m | 4,549 | utf_8 | f992891144a934ab4edffde2a692e435 | %%*******************************************************************
%% schurmat_sblk: compute Schur complement matrix corresponding to
%% SDP blocks.
%%
%% symm = 0, HKM
%% = 1, NT
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
... |
github | noureldien/RecommenderSystem-master | blktrace.m | .m | RecommenderSystem-master/cvx/sdpt3/Solver/blktrace.m | 2,084 | utf_8 | 6a5c3d9ff74073a8e864c246727eaa86 | %%**********************************************************************
%% blktrace: compute <X1,Z1> + ... + <Xp,Zp>
%%
%% SDPT3: version 3.1
%% Copyright (c) 1997 by
%% K.C. Toh, M.J. Todd, R.H. Tutuncu
%% Last Modified: 16 Sep 2004
%%**********************************************************************
function tr... |
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