Fetching the paper…
Reading the bibliography…
This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms.
A stochastic approximation method
H. Robbins and S. Monro · 1951
Earlier work this paper cites.
An algorithm for quadratic programming
M. Frank and P. Wolfe · 1956
Earlier work this paper cites.
Partitions of mass-distributions and of convex bodies by hyperplanes
B. Grünbaum · 1960
Earlier work this paper cites.
On an algorithm for the minimization of convex functions
A. Levin · 1965
Earlier work this paper cites.
Location of the maximum on unimodal surfaces
D. Newman · 1965
Earlier work this paper cites.
Convex Analysis
R. Rockafellar · 1970
Earlier work this paper cites.
Conditional gradient algorithms with open loop step size rules
J. C. Dunn and S. Harshbarger · 1978
Earlier work this paper cites.
Orth-method for smooth convex optimization
A. Nemirovski · 1982
Earlier work this paper cites.
Problem Complexity and Method Efficiency in Optimization
A. Nemirovski and D. Yudin · 1983
Earlier work this paper cites.
A method of solving a convex programming problem with convergence rate o( 1 / k 2 1/k^{2} )
Y. Nesterov · 1983
Earlier work this paper cites.
A new polynomial-time algorithm for linear programming
N. Karmarkar · 1984
Earlier work this paper cites.
A linear-time median-finding algorithm for projecting a vector on the simplex of rn
N. Maculan and G. G. de Paula · 1989
Earlier work this paper cites.
A new algorithm for minimizing convex functions over convex sets
P. M. Vaidya · 1989
Earlier work this paper cites.
1990 shannon lecture
T. M. Cover · 1992
Earlier work this paper cites.
A simple lemma on greedy approximation in hilbert space and convergence rates for projection pursuit regression and neural network training
L. K. Jones · 1992
Earlier work this paper cites.
Interior-point polynomial algorithms in convex programming
Y. Nesterov and A. Nemirovski · 1994
Earlier work this paper cites.
Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
M. Goemans and D. Williamson · 1995
Earlier work this paper cites.
A sublinear-time randomized approximation algorithm for matrix games
M. D. Grigoriadis and L. G. Khachiyan · 1995
Earlier work this paper cites.
Information-based complexity of convex programming
A. Nemirovski · 1995
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
R. Tibshirani · 1996
Earlier work this paper cites.
A new algorithm for minimizing convex functions over convex sets
P. M. Vaidya · 1996
Earlier work this paper cites.
Quality of semidefinite relaxation for nonconvex quadratic optimization
Y. Nesterov · 1997
Earlier work this paper cites.
Towards a practical volumetric cutting plane method for convex programming
K. M. Anstreicher · 1998
Earlier work this paper cites.
Hit-and-run mixes fast
L. Lovász · 1998
Earlier work this paper cites.
Random vectors in the isotropic position
M. Rudelson · 1999
Earlier work this paper cites.
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
A. Ben-Tal and A. Nemirovski · 2001
Earlier work this paper cites.
The Elements of Statistical Learning
T. Hastie, R. Tibshirani, and J. Friedman · 2001
Cited alongside, same era.
A mathematical view of interior-point methods in convex optimization , volume 3
J. Renegar · 2001
Cited alongside, same era.
Learning with kernels
B. Schölkopf and A. Smola · 2002
Cited alongside, same era.
Mirror Descent and nonlinear projected subgradient methods for convex optimization
A. Beck and M. Teboulle · 2003
Cited alongside, same era.
Optimal rates of aggregation
A. Tsybakov · 2003
Cited alongside, same era.
Solving convex programs by random walks
D. Bertsimas and S. Vempala · 2004
Cited alongside, same era.
Convex Optimization
Convergence rates of inexact proximal-gradient methods for convex optimization
M. Schmidt, N. Le Roux, and F. Bach · 2011
Later among the works it cites.
Optimization with sparsity-inducing penalties
F. Bach, R. Jenatton, J. Mairal, and G. Obozinski · 2012
Later among the works it cites.
Regret analysis of stochastic and nonstochastic multi-armed bandit problems
S. Bubeck and N. Cesa-Bianchi · 2012
Later among the works it cites.
Sublinear optimization for machine learning
K. Clarkson, E. Hazan, and D. Woodruff · 2012
Later among the works it cites.
Optimal distributed online prediction using mini-batches
O. Dekel, R. Gilad-Bachrach, O. Shamir, and L. Xiao · 2012
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. Boyd and L. Vandenberghe · 2004
Cited alongside, same era.
Prediction, Learning, and Games
N. Cesa-Bianchi and G. Lugosi · 2006
Cited alongside, same era.
Numerical Optimization
J. Nocedal and S. J. Wright · 2006
Cited alongside, same era.
Exact regularization of convex programs
M. P. Friedlander and P. Tseng · 2007
Cited alongside, same era.
Gradient methods for minimizing composite objective function
Y. Nesterov · 2007
Cited alongside, same era.
Smooth optimization with approximate gradient
A. d’Aspremont · 2008
Cited alongside, same era.
S. Lacoste-Julien, M. Schmidt, and F. Bach · 2012
Later among the works it cites.
A stochastic gradient method with an exponential convergence rate for strongly-convex optimization with finite training sets
N. Le Roux, M. Schmidt, and F. Bach · 2012
Later among the works it cites.
Efficiency of coordinate descent methods on huge-scale optimization problems
Y. Nesterov · 2012
Later among the works it cites.
Parallel coordinate descent methods for big data optimization
P. Richtárik and M. Takác · 2012
Later among the works it cites.
Learning with submodular functions: A convex optimization perspective
F. Bach · 2013
Later among the works it cites.
Non-strongly-convex smooth stochastic approximation with convergence rate o(1/n)
F. Bach and E. Moulines · 2013
Later among the works it cites.
Revisiting frank-wolfe: Projection-free sparse convex optimization
M. Jaggi · 2013
Later among the works it cites.
Low-rank matrix completion using alternating minimization
P. Jain, P. Netrapalli, and S. Sanghavi · 2013
Later among the works it cites.
Accelerating stochastic gradient descent using predictive variance reduction
R. Johnson and T. Zhang · 2013
Later among the works it cites.
Path finding i :solving linear programs with Õ(sqrt(rank)) linear system solves
Y.-T. Lee and A. Sidford · 2013
Later among the works it cites.
Proximal algorithms
N. Parikh and S. Boyd · 2013
Later among the works it cites.
A lower bound for the optimization of finite sums
A. Agarwal and L. Bottou · 2014
Closest in time.
Linear coupling: An ultimate unification of gradient and mirror descent
Z. Allen-Zhu and L. Orecchia · 2014
Closest in time.
Regret in online combinatorial optimization
J.Y. Audibert, S. Bubeck, and G. Lugosi · 2014
Closest in time.
Sum of squares upper bounds, lower bounds, and open questions
B. Barak · 2014
Closest in time.
The entropic barrier: a simple and optimal universal self-concordant barrier
S. Bubeck and R. Eldan · 2014
Closest in time.
Saga: A fast incremental gradient method with support for non-strongly convex composite objectives
A. Defazio, F. Bach, and S. Lacoste-Julien · 2014
Closest in time.
Understanding Machine Learning: From Theory to Algorithms
S. Shalev-Shwartz and S. Ben-David · 2014
Closest in time.
A differential equation for modeling nesterov’s accelerated gradient method: Theory and insights
W. Su, S. Boyd, and E. Candès · 2014
Closest in time.
Stochastic primal-dual coordinate method for regularized empirical risk minimization
Y. Zhang and L. Xiao · 2014
Closest in time.
A faster cutting plane method and its implications for combinatorial and convex optimization
Y.-T. Lee, A. Sidford, and S. C.-W Wong · 2015
Closest in time.