Fetching the paper…
Reading the bibliography…
We study --both in theory and practice-- the use of momentum motions in classic iterative hard thresholding (IHT) methods.
Methods of conjugate gradients for solving linear systems
M. Hestenes and E. Stiefel · 1952
Earlier work this paper cites.
Some methods of speeding up the convergence of iteration methods
B. Polyak · 1964
Earlier work this paper cites.
Convergence theory in nonlinear programming
P. Wolfe · 1970
Earlier work this paper cites.
Finding the point of a polyhedron closest to the origin
B. Mitchell, V. Demyanov, and V. Malozemov · 1974
Earlier work this paper cites.
A method of solving a convex programming problem with convergence rate O ( 1 k 2 ) (\tfrac{1}{k^{2}})
Y. Nesterov · 1983
Earlier work this paper cites.
The n n -th power of a 2 × 2 2\times 2 matrix
K. Williams · 1992
Earlier work this paper cites.
Iterative solution methods
O. Axelsson · 1996
Earlier work this paper cites.
Atomic decomposition by basis pursuit
S. Chen, D. Donoho, and M. Saunders · 2001
Earlier work this paper cites.
Adaptive overrelaxed bound optimization methods
R. Salakhutdinov and S. Roweis · 2003
Earlier work this paper cites.
Neighborliness of randomly projected simplices in high dimensions
D. Donoho and J. Tanner · 2005
Earlier work this paper cites.
A new TwIST: Two-step iterative shrinkage/thresholding algorithms for image restoration
J. Bioucas-Dias and M. Figueiredo · 2007
Earlier work this paper cites.
A unified framework for high-dimensional analysis of m m -estimators with decomposable regularizers
S. Negahban, B. Yu, M. Wainwright, and P. Ravikumar · 2009
Earlier work this paper cites.
Iterative hard thresholding for compressed sensing
T. Blumensath and M. Davies · 2009
Earlier work this paper cites.
Gradient descent with sparsification: an iterative algorithm for sparse recovery with restricted isometry property
R. Garg and R. Khandekar · 2009
Earlier work this paper cites.
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
D. Needell and J. Tropp · 2009
Earlier work this paper cites.
A fast iterative shrinkage-thresholding algorithm for linear inverse problems
A. Beck and M. Teboulle · 2009
Earlier work this paper cites.
Adaptive forward-backward greedy algorithm for sparse learning with linear models
T. Zhang · 2009
Earlier work this paper cites.
Group lasso with overlap and graph lasso
L. Jacob, G. Obozinski, and J.-P. Vert · 2009
Earlier work this paper cites.
Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm
K. Clarkson · 2010
Earlier work this paper cites.
Guaranteed rank minimization via singular value projection
P. Jain, R. Meka, and I. Dhillon · 2010
Earlier work this paper cites.
Fast global convergence rates of gradient methods for high-dimensional statistical recovery
A. Agarwal, S. Negahban, and M. Wainwright · 2010
Earlier work this paper cites.
ECME thresholding methods for sparse signal reconstruction
K. Qiu and A. Dogandzic · 2010
Earlier work this paper cites.
Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
B. Recht, M. Fazel, and P. Parrilo · 2010
Cited alongside, same era.
Recipes on hard thresholding methods
A. Kyrillidis and V. Cevher · 2011
Cited alongside, same era.
Hard thresholding pursuit: an algorithm for compressive sensing
S. Foucart · 2011
Cited alongside, same era.
Convergence rates of inexact proximal-gradient methods for convex optimization
M. Schmidt, N. Roux, and F. Bach · 2011
Cited alongside, same era.
Templates for convex cone problems with applications to sparse signal recovery
S. Becker, E. Candès, and M. Grant · 2011
Cited alongside, same era.
Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
S. Shalev-Shwartz and T. Zhang · 2014
Later among the works it cites.
The computational complexity of the restricted isometry property, the nullspace property, and related concepts in compressed sensing
A. Tillmann and M. Pfetsch · 2014
Later among the works it cites.
On the global linear convergence of Frank-Wolfe optimization variants
S. Lacoste-Julien and M. Jaggi · 2015
Later among the works it cites.
On the minimization over sparse symmetric sets: projections, optimality conditions, and algorithms
A. Beck and N. Hallak · 2015
Later among the works it cites.
Structured sparsity: Discrete and convex approaches
A. Kyrillidis, L. Baldassarre, M. El Halabi, Q. Tran-Dinh, and V. Cevher · 2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Submodular meets spectral: Greedy algorithms for subset selection, sparse approximation and dictionary selection
A. Das and D. Kempe · 2011
Cited alongside, same era.
Sampling and reconstructing signals from a union of linear subspaces
T. Blumensath · 2011
Cited alongside, same era.
Iterative projections for signal identification on manifolds: Global recovery guarantees
P. Shah and V. Chandrasekaran · 2011
Cited alongside, same era.
The convex geometry of linear inverse problems
V. Chandrasekaran, B. Recht, P. Parrilo, and A. Willsky · 2012
Cited alongside, same era.
Structured sparsity through convex optimization
F. Bach, R. Jenatton, J. Mairal, and G. Obozinski · 2012
Cited alongside, same era.
Accelerated iterative hard thresholding
T. Blumensath · 2012
Cited alongside, same era.
J. Blanchard, J. Tanner, and K. Wei · 2015
Later among the works it cites.
Fast iterative hard thresholding for compressed sensing
K. Wei · 2015
Later among the works it cites.
Adaptive restart for accelerated gradient schemes
B. O’Donoghue and E. Candes · 2015
Later among the works it cites.
Accelerated proximal gradient methods for nonconvex programming
H. Li and Z. Lin · 2015
Later among the works it cites.
Faster rates for the Frank-Wolfe method over strongly-convex sets
D. Garber and E. Hazan · 2015
Later among the works it cites.
Approximation algorithms for model-based compressive sensing
C. Hegde, P. Indyk, and L. Schmidt · 2015
Later among the works it cites.
Structured sparse regression via greedy hard thresholding
P. Jain, N. Rao, and I. Dhillon · 2016
Later among the works it cites.
Accelerated gradient methods for nonconvex nonlinear and stochastic programming
S. Ghadimi and G. Lan · 2016
Later among the works it cites.
Accelerated methods for non-convex optimization
Y. Carmon, J. Duchi, O. Hinder, and A. Sidford · 2016
Later among the works it cites.
Finding approximate local minima for nonconvex optimization in linear time
N. Agarwal, Z. Allen-Zhu, B. Bullins, E. Hazan, and T. Ma · 2016
Later among the works it cites.
A lyapunov analysis of momentum methods in optimization
A. Wilson, B. Recht, and M. Jordan · 2016
Later among the works it cites.
Dropping convexity for faster semi-definite optimization
S. Bhojanapalli, A. Kyrillidis, and S. Sanghavi · 2016
Later among the works it cites.
Finding low-rank solutions to matrix problems, efficiently and provably
D. Park, A. Kyrillidis, C. Caramanis, and S. Sanghavi · 2016
Later among the works it cites.
Gradient descent with nonconvex constraints: Local concavity determines convergence
R. F. Barber and W. Ha · 2017
Closest in time.
Catalyst acceleration for gradient-based non-convex optimization
C. Paquette, H. Lin, D. Drusvyatskiy, J. Mairal, and Z. Harchaoui · 2017
Closest in time.
Integration methods and accelerated optimization algorithms
D. Scieur, V. Roulet, F. Bach, and A. d’Aspremont · 2017
Closest in time.