20 citations · 48 across the 6 of their papers we have counts for
5 papers · 1 filter
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis
Koulik Khamaru, Ashwin Pananjady, Feng Ruan +2
We address the problem of policy evaluation in discounted Markov decision processes, and provide instance-dependent guarantees on the -error under a generative model.…
Instance-dependent -bounds for policy evaluation in tabular reinforcement learning
Ashwin Pananjady, Martin J. Wainwright
Markov reward processes (MRPs) are used to model stochastic phenomena arising in operations research, control engineering, robotics, and artificial intelligence, as well as communi…
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation
Avishek Ghosh, Ashwin Pananjady, Adityanand Guntuboyina +1
Max-affine regression refers to a model where the unknown regression function is modeled as a maximum of unknown affine functions for a fixed . This generalizes linea…
Towards Optimal Estimation of Bivariate Isotonic Matrices with Unknown Permutations
Cheng Mao, Ashwin Pananjady, Martin J. Wainwright
Many applications, including rank aggregation, crowd-labeling, and graphon estimation, can be modeled in terms of a bivariate isotonic matrix with unknown permutations acting on it…
Breaking the Barrier: Faster Rates for Permutation-based Models in Polynomial Time
Cheng Mao, Ashwin Pananjady, Martin J. Wainwright
Many applications, including rank aggregation and crowd-labeling, can be modeled in terms of a bivariate isotonic matrix with unknown permutations acting on its rows and columns. W…