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most citedEven Faster Accelerated Coordinate Descent Using Non-Uniform Sampling

100 citations · 462 across the 26 of their papers we have counts for

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Showing 2014 · math.OCShow all

5 papers · 2 filters

math.OC2014★ 16 cited

Coordinate Descent with Arbitrary Sampling II: Expected Separable Overapproximation

Zheng Qu, Peter Richtárik

The design and complexity analysis of randomized coordinate descent methods, and in particular of variants which update a random subset (sampling) of coordinates in each iteration,…

math.OC2014★ 33 cited

Coordinate Descent with Arbitrary Sampling I: Algorithms and Complexity

Zheng Qu, Peter Richtárik

We study the problem of minimizing the sum of a smooth convex function and a convex block-separable regularizer and propose a new randomized coordinate descent method, which we cal…

math.OC2014★ 49 cited

Randomized Dual Coordinate Ascent with Arbitrary Sampling

Zheng Qu, Peter Richtárik, Tong Zhang

We study the problem of minimizing the average of a large number of smooth convex functions penalized with a strongly convex regularizer. We propose and analyze a novel primal-dual…

math.OC2014

Fast Distributed Coordinate Descent for Non-Strongly Convex Losses

Olivier Fercoq, Zheng Qu, Peter Richtárik +1

We propose an efficient distributed randomized coordinate descent method for minimizing regularized non-strongly convex loss functions. The method attains the optimal co…

math.OC2014★ 4 cited

Bundle-based pruning in the max-plus curse of dimensionality free method

Stephane Gaubert, Zheng Qu, Srinivas Sridharan

Recently a new class of techniques termed the max-plus curse of dimensionality-free methods have been developed to solve nonlinear optimal control problems. In these methods the di…