2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.DB2012
Scaling Multiple-Source Entity Resolution using Statistically Efficient Transfer Learning
Sahand Negahban, Benjamin I. P. Rubinstein, Jim Gemmell
We consider a serious, previously-unexplored challenge facing almost all approaches to scaling up entity resolution (ER) to multiple data sources: the prohibitive cost of labeling…
stat.ML2012
Stochastic optimization and sparse statistical recovery: An optimal algorithm for high dimensions
Alekh Agarwal, Sahand Negahban, Martin J. Wainwright
We develop and analyze stochastic optimization algorithms for problems in which the expected loss is strongly convex, and the optimum is (approximately) sparse. Previous approaches…
math.ST2009★ 2 cited
Simultaneous support recovery in high dimensions: Benefits and perils of block -regularization
S. Negahban, M. J. Wainwright
Consider the use of -regularized regression for joint estimation of a $\pdim \times \numreg$ matrix of regression coefficients. We analyze the high-dimensio…