ASAGA: Asynchronous Parallel SAGA

Parallel and Distributed Computation: Numerical Methods

D. P. Bertsekas and J. N. Tsitsiklis · 1989

Earlier work this paper cites.

A parallel mixture of svms for very large scale problems

R. Collobert, S. Bengio, and Y. Bengio · 2002

Earlier work this paper cites.

RCV1: A new benchmark collection for text categorization research

D. D. Lewis, Y. Yang, T. G. Rose, and F. Li · 2004

Earlier work this paper cites.

Identifying suspicious URLs: an application of large-scale online learning

J. Ma, L. K. Saul, S. Savage, and G. M. Voelker · 2009

Earlier work this paper cites.

Hogwild: a lock-free approach to parallelizing stochastic gradient descent

F. Niu, B. Recht, C. Re, and S. Wright · 2011

Earlier work this paper cites.

A stochastic gradient method with an exponential convergence rate for finite training sets

N. Le Roux, M. Schmidt, and F. Bach · 2012

Earlier work this paper cites.

Accelerating stochastic gradient descent using predictive variance reduction

R. Johnson and T. Zhang · 2013

Earlier work this paper cites.

Semi-stochastic gradient descent methods

Original

J. Konecny and P. Richtarik · 2013

Cited alongside, same era.

Stochastic dual coordinate ascent methods for regularized loss

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.

Taming the wild: a unified analysis of Hogwild!-style algorithms

C. De Sa, C. Zhang, K. Olukotun, and C. Ré · 2015

Cited alongside, same era.

Asynchronous stochastic convex optimization

J. C. Duchi, S. Chaturapruek, and C. Ré · 2015

Cited alongside, same era.

Variance reduced stochastic gradient descent with neighbors

T. Hofmann, A. Lucchi, S. Lacoste-Julien, and B. McWilliams · 2015

Asynchronous parallel stochastic gradient for nonconvex optimization

X. Lian, Y. Huang, Y. Li, and J. Liu · 2015

Later among the works it cites.

An asynchronous parallel stochastic coordinate descent algorithm

J. Liu, S. J. Wright, C. Ré, V. Bittorf, and S. Sridhar · 2015

Later among the works it cites.

Adding vs. averaging in distributed primal-dual optimization

C. Ma, V. Smith, M. Jaggi, M. I. Jordan, P. Richtarik, and M. Takac · 2015

Later among the works it cites.

Perturbed iterate analysis for asynchronous stochastic optimization

Original

H. Mania, X. Pan, D. Papailiopoulos, B. Recht, K. Ramchandran, and M. I. Jordan · 2015

Later among the works it cites.

On variance reduction in stochastic gradient descent and its asynchronous variants

S. J. Reddi, A. Hefny, S. Sra, B. Póczos, and A. Smola · 2015

Later among the works it cites.