Online Markov Decision Processes with Aggregate Bandit Feedback, 2021
Unknown mixing times in apprenticeship and reinforcement learning, UAI, 2020
Near-optimal Regret Bounds for Stochastic Shortest Path, ICML, 2020
Logarithmic regret for learning linear quadratic regulators efficiently, ICML, 2020
Apprenticeship Learning via Frank-Wolfe, AAAI, 2020
Learning to Screen, NeurIPS, 2019
Learning Linear-Quadratic Regulators Efficiently with only √T Regret, ICML, 2019
Online Linear Quadratic Control, ICML, 2018
Planning and Learning with Stochastic Action Sets, IJCAI, 2018
Tight Bounds for Bandit Combinatorial Optimization, COLT, 2017
Online Learning with Feedback Graphs Without the Graphs, ICML, 2016
Following the Perturbed Leader for Online Structured Learning, ICML, 2015
Research Experience
Senior lecturer at the School of Electrical Engineering - Systems at Tel-Aviv University; Researcher at Google Research Tel-Aviv.
Education
PhD in Machine Learning from the Faculty of IE&M at the Technion, supervised by Prof. Tamir Hazan.
Background
Research interests include statistical learning, online learning, and decision-making under uncertainty, with a particular focus on the intersection between online learning and reinforcement learning.