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09/04/2023
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
In this work, we study first-order algorithms for solving Bilevel Optimi...
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06/15/2023
Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
Modern machine learning models deployed in the wild can encounter both c...
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01/26/2023
A Fully First-Order Method for Stochastic Bilevel Optimization
We consider stochastic unconstrained bilevel optimization problems when ...
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10/05/2022
Tractable Optimality in Episodic Latent MABs
We consider a multi-armed bandit problem with M latent contexts, where a...
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10/05/2022
Reward-Mixing MDPs with a Few Latent Contexts are Learnable
We consider episodic reinforcement learning in reward-mixing Markov deci...
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01/30/2022
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms
Motivated by online recommendation systems, we propose the problem of fi...
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10/07/2021
Reinforcement Learning in Reward-Mixing MDPs
Learning a near optimal policy in a partially observable system remains ...
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02/09/2021
RL for Latent MDPs: Regret Guarantees and a Lower Bound
In this work, we consider the regret minimization problem for reinforcem...
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01/27/2021
On the computational and statistical complexity of over-parameterized matrix sensing
We consider solving the low rank matrix sensing problem with Factorized ...
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06/04/2020
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
We study the convergence rates of the EM algorithm for learning two-comp...
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02/02/2020
EM Algorithm is Sample-Optimal for Learning Mixtures of Well-Separated Gaussians
We consider the problem of spherical Gaussian Mixture models with k ≥ 3 ...
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05/28/2019
EM Converges for a Mixture of Many Linear Regressions
We study the convergence of the Expectation-Maximization (EM) algorithm ...
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10/12/2018