activity
20122022
most citedSimple random search provides a competitive approach to reinforcement learning

162 citations · 442 across the 14 of their papers we have counts for

collaborators

16 papers

math.OC2022★ 4 cited

Model Predictive Control via On-Policy Imitation Learning

Kwangjun Ahn, Zakaria Mhammedi, Horia Mania +2

In this paper, we leverage the rapid advances in imitation learning, a topic of intense recent focus in the Reinforcement Learning (RL) literature, to develop new sample complexity…

math.ST2021★ 2 cited

Time varying regression with hidden linear dynamics

Ali Jadbabaie, Horia Mania, Devavrat Shah +1

We revisit a model for time-varying linear regression that assumes the unknown parameters evolve according to a linear dynamical system. Counterintuitively, we show that when the u…

cs.LG2020★ 3 cited

Why do classifier accuracies show linear trends under distribution shift?

Horia Mania, Suvrit Sra

Recent studies of generalization in deep learning have observed a puzzling trend: accuracies of models on one data distribution are approximately linear functions of the accuracies…

cs.LG2020★ 21 cited

Bandit Learning in Decentralized Matching Markets

Lydia T. Liu, Feng Ruan, Horia Mania +1

We study two-sided matching markets in which one side of the market (the players) does not have a priori knowledge about its preferences for the other side (the arms) and is requir…

stat.ML2020★ 28 cited

Active Learning for Nonlinear System Identification with Guarantees

Horia Mania, Michael I. Jordan, Benjamin Recht

While the identification of nonlinear dynamical systems is a fundamental building block of model-based reinforcement learning and feedback control, its sample complexity is only un…

cs.LG2019★ 8 cited

Competing Bandits in Matching Markets

Lydia T. Liu, Horia Mania, Michael I. Jordan

Stable matching, a classical model for two-sided markets, has long been studied with little consideration for how each side's preferences are learned. With the advent of massive on…