activity
20152020
most citedVariational consensus Monte Carlo

15 citations · 24 across the 4 of their papers we have counts for

collaborators

5 papers

math.ST20202 cited

Lower bounds in multiple testing: A framework based on derandomized proxies

Max Rabinovich, Michael I. Jordan, Martin J. Wainwright

The large bulk of work in multiple testing has focused on specifying procedures that control the false discovery rate (FDR), with relatively less attention being paid to the corres…

math.ST2017

Optimal Rates and Tradeoffs in Multiple Testing

Maxim Rabinovich, Aaditya Ramdas, Michael I. Jordan +1

Multiple hypothesis testing is a central topic in statistics, but despite abundant work on the false discovery rate (FDR) and the corresponding Type-II error concept known as the f…

stat.ML20157 cited

On the accuracy of self-normalized log-linear models

Jacob Andreas, Maxim Rabinovich, Dan Klein +1

Calculation of the log-normalizer is a major computational obstacle in applications of log-linear models with large output spaces. The problem of fast normalizer computation has th…

stat.ML201515 cited

Variational consensus Monte Carlo

Maxim Rabinovich, Elaine Angelino, Michael I. Jordan

Practitioners of Bayesian statistics have long depended on Markov chain Monte Carlo (MCMC) to obtain samples from intractable posterior distributions. Unfortunately, MCMC algorithm…

cs.CL2015

Online Inference for Relation Extraction with a Reduced Feature Set

Maxim Rabinovich, Cédric Archambeau

Access to web-scale corpora is gradually bringing robust automatic knowledge base creation and extension within reach. To exploit these large unannotated---and extremely difficult…