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06/28/2023
Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time
Despite recent theoretical progress on the non-convex optimization of tw...
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04/29/2023
Toward L_∞-recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields
Many machine learning applications require learning a function with a sm...
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01/26/2023
Model-based Offline Reinforcement Learning with Local Misspecification
We present a model-based offline reinforcement learning policy performan...
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11/21/2022
First Steps Toward Understanding the Extrapolation of Nonlinear Models to Unseen Domains
Real-world machine learning applications often involve deploying neural ...
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06/06/2022
Asymptotic Instance-Optimal Algorithms for Interactive Decision Making
Past research on interactive decision making problems (bandits, reinforc...
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07/21/2021
Design of Experiments for Stochastic Contextual Linear Bandits
In the stochastic linear contextual bandit setting there exist several m...
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02/08/2021
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature
This paper studies model-based bandit and reinforcement learning (RL) wi...
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08/21/2020
Refined Analysis of FPL for Adversarial Markov Decision Processes
We consider the adversarial Markov Decision Process (MDP) problem, where...
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07/09/2020
Multinomial Logit Bandit with Low Switching Cost
We study multinomial logit bandit with limited adaptivity, where the alg...
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10/14/2019
Bootstrapping the Expressivity with Model-based Planning
We compare the model-free reinforcement learning with the model-based ap...
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09/05/2019
√(n)-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank
In this paper, we consider the problem of online learning of Markov deci...
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06/10/2019
Exploration via Hindsight Goal Generation
Goal-oriented reinforcement learning has recently been a practical frame...
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01/27/2019