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02/02/2023
A Theoretical Justification for Image Inpainting using Denoising Diffusion Probabilistic Models
We provide a theoretical justification for sample recovery using diffusi...
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03/23/2022
Minimax Regret for Cascading Bandits
Cascading bandits model the task of learning to rank K out of L items ov...
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02/02/2021
A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants
This paper develops an unified framework to study finite-sample converge...
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09/14/2020
Hellinger KL-UCB based Bandit Algorithms for Markovian and i.i.d. Settings
In the regret-based formulation of multi-armed bandit (MAB) problems, ex...
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03/06/2020
Contextual Blocking Bandits
We study a novel variant of the multi-armed bandit problem, where at eac...
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02/19/2020
Warm Starting Bandits with Side Information from Confounded Data
We study a variant of the multi-armed bandit problem where side informat...
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02/12/2020
Distribution-Agnostic Model-Agnostic Meta-Learning
The Model-Agnostic Meta-Learning (MAML) algorithm <cit.> has been celebr...
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02/02/2018
