260 citations · 1.8k across the 63 of their papers we have counts for
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stat.ML2013★ 19 cited
On Optimal Probabilities in Stochastic Coordinate Descent Methods
Peter Richtárik, Martin Takáč
We propose and analyze a new parallel coordinate descent method---`NSync---in which at each iteration a random subset of coordinates is updated, in parallel, allowing for the subse…
stat.ML2013★ 195 cited
Distributed Coordinate Descent Method for Learning with Big Data
Peter Richtárik, Martin Takáč
In this paper we develop and analyze Hydra: HYbriD cooRdinAte descent method for solving loss minimization problems with big data. We initially partition the coordinates (features)…
cs.LG2013★ 89 cited
Mini-Batch Primal and Dual Methods for SVMs
Martin Takáč, Avleen Bijral, Peter Richtárik +1
We address the issue of using mini-batches in stochastic optimization of SVMs. We show that the same quantity, the spectral norm of the data, controls the parallelization speedup o…