Fetching the paper…
Reading the bibliography…
We develop a family of accelerated stochastic algorithms that minimize sums of convex functions.
Monotone operators and the proximal point algorithm
R. T. Rockafellar · 1976
Earlier work this paper cites.
A method of solving a convex programming problem with convergence rate O ( 1 / k 2 ) {O}(1/k^{2})
Y. Nesterov · 1983
Earlier work this paper cites.
New proximal point algorithms for convex minimization
O. Guler · 1992
Earlier work this paper cites.
Introductory Lectures on Convex Optimization: A Basic Course
Y. Nesterov · 2004
Earlier work this paper cites.
Random features for large-scale kernel machines
A. Rahimi and B. Recht · 2007
Earlier work this paper cites.
The tradeoffs of large scale learning
L. Bottou and O. Bousquet · 2008
Earlier work this paper cites.
A randomized kaczmarz algorithm with exponential convergence
T. Strohmer and R. Vershynin · 2009
Earlier work this paper cites.
Distributed optimization and statistical learning via the alternating direction method of multipliers
S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein · 2011
Earlier work this paper cites.
A stochastic gradient method with an exponential convergence rate for finite training sets
N. L. Roux, M. Schmidt, and F. Bach · 2012
Cited alongside, same era.
Multiplying matrices faster than Coppersmith-Winograd
V. V. Williams · 2012
Cited alongside, same era.
Accelerating stochastic gradient descent using predictive variance reduction
R. Johnson and T. Zhang · 2013
Cited alongside, same era.
Efficient accelerated coordinate descent methods and faster algorithms for solving linear systems
Y. T. Lee and A. Sidford · 2013
Cited alongside, same era.
Iterative row sampling
M. Li, G. L. Miller, and R. Peng · 2013
Cited alongside, same era.
OSNAP: Faster numerical linear algebra algorithms via sparser subspace embeddings
J. Nelson and H. L. Nguyen · 2013
Cited alongside, same era.
An accelerated proximal coordinate gradient method
Q. Lin, Z. Lu, and L. Xiao · 2014
Later among the works it cites.
Stochastic gradient descent, weighted sampling, and the randomized kaczmarz algorithm
D. Needell, N. Srebro, and R. Ward · 2014
Later among the works it cites.
Proximal algorithms
N. Parikh and S. Boyd · 2014
Later among the works it cites.
Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
S. Shalev-Shwartz and T. Zhang · 2014
Later among the works it cites.
A proximal stochastic gradient method with progressive variance reduction
L. Xiao and T. Zhang · 2014
Later among the works it cites.
Uniform sampling for matrix approximation
M. B. Cohen, Y. T. Lee, C. Musco, C. Musco, R. Peng, and A. Sidford · 2015
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Stochastic dual coordinate ascent methods for regularized loss minimization
S. Shalev-Shwartz and T. Zhang · 2013
Cited alongside, same era.
Saga: A fast incremental gradient method with support for non-strongly convex composite objectives
A. Defazio, F. Bach, and S. Lacoste-Julien · 2014
Cited alongside, same era.
Closest in time.
A universal catalyst for first-order optimization
H. Lin, J. Mairal, and Z. Harchaoui · 2015
Closest in time.