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07/08/2023
Efficient Model-Free Exploration in Low-Rank MDPs
A major challenge in reinforcement learning is to develop practical, sam...
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06/19/2023
Projection-Free Online Convex Optimization via Efficient Newton Iterations
This paper presents new projection-free algorithms for Online Convex Opt...
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04/27/2023
Exponential Stochastic Inequality
We develop the concept of exponential stochastic inequality (ESI), a nov...
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04/12/2023
Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
We study the design of sample-efficient algorithms for reinforcement lea...
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11/02/2022
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization
The aim of this paper is to design computationally-efficient and optimal...
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10/17/2022
Model Predictive Control via On-Policy Imitation Learning
In this paper, we leverage the rapid advances in imitation learning, a t...
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05/23/2022
Exploiting the Curvature of Feasible Sets for Faster Projection-Free Online Learning
In this paper, we develop new efficient projection-free algorithms for O...
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02/15/2022
Damped Online Newton Step for Portfolio Selection
We revisit the classic online portfolio selection problem, where at each...
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11/10/2021
Efficient Projection-Free Online Convex Optimization with Membership Oracle
In constrained convex optimization, existing methods based on the ellips...
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11/28/2020
Risk-Monotonicity in Statistical Learning
Acquisition of data is a difficult task in many applications of machine ...
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10/08/2020
Learning the Linear Quadratic Regulator from Nonlinear Observations
We introduce a new problem setting for continuous control called the LQR...
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06/26/2020
PAC-Bayesian Bound for the Conditional Value at Risk
Conditional Value at Risk (CVaR) is a family of "coherent risk measures"...
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02/27/2020
Lipschitz and Comparator-Norm Adaptivity in Online Learning
We study Online Convex Optimization in the unbounded setting where neith...
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05/31/2019
PAC-Bayes Un-Expected Bernstein Inequality
We present a new PAC-Bayesian generalization bound. Standard bounds cont...
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02/27/2019
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning
We aim to design adaptive online learning algorithms that take advantage...
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02/20/2018
Constant Regret, Generalized Mixability, and Mirror Descent
We consider the setting of prediction with expert advice; a learner make...
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02/20/2018
Generalized Mixability Constant Regret, Generalized Mixability, and Mirror Descent
We consider the setting of prediction with expert advice; a learner make...
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03/04/2017