Chris Re

2 accepted papers

2018

Accelerated Stochastic Power Iteration

Peng Xu, Bryan He, Christopher De Sa, Ioannis Mitliagkas, Chris Re

AISTATS 2018poster

Principal component analysis (PCA) is one of the most powerful tools for analyzing matrices in machine learning. In this paper, we study methods to accelerate power iteration in the stochastic setting by adding a momentum term. While in the deterministic setting, power iteration with momentum has op…

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2016

Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling

Christopher De Sa, Chris Re, Kunle Olukotun

ICML 2016poster

Gibbs sampling is a Markov chain Monte Carlo technique commonly used for estimating marginal distributions. To speed up Gibbs sampling, there has recently been interest in parallelizing it by executing asynchronously. While empirical results suggest that many models can be efficiently sampled asynch…

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