937 citations · 4k across the 76 of their papers we have counts for
12 papers · 1 filter
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
Aditya Grover, Jiaming Song, Alekh Agarwal +4
A learned generative model often produces biased statistics relative to the underlying data distribution. A standard technique to correct this bias is importance sampling, where sa…
A Contextual Bandit Bake-off
Alberto Bietti, Alekh Agarwal, John Langford
Contextual bandit algorithms are essential for solving many real-world interactive machine learning problems. Despite multiple recent successes on statistically and computationally…
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudik
We study the off-policy evaluation problem---estimating the value of a target policy using data collected by another policy---under the contextual bandit model. We consider the gen…
A Lower Bound for the Optimization of Finite Sums
Alekh Agarwal, Leon Bottou
This paper presents a lower bound for optimizing a finite sum of functions, where each function is -smooth and the sum is -strongly convex. We show that no algorithm can…
A Clustering Approach to Learn Sparsely-Used Overcomplete Dictionaries
Alekh Agarwal, Animashree Anandkumar, Praneeth Netrapalli
We consider the problem of learning overcomplete dictionaries in the context of sparse coding, where each sample selects a sparse subset of dictionary elements. Our main result is…
Oracle inequalities for computationally adaptive model selection
Alekh Agarwal, Peter L. Bartlett, John C. Duchi
We analyze general model selection procedures using penalized empirical loss minimization under computational constraints. While classical model selection approaches do not conside…