Probability Theory

Heavy-tail behaviour of SGD - Part 1
Event Weekly OSI Lab Seminar Short summary In this seminar, I will talk about a recent line of works that propose to analyze SGD under heavy-tail noise assumptions. Abstract One of the popular ways of analyzing the behavior of SGD and SGDm(SGD with momentum) is by considering it as a discretization of Langevin-type SDE.
Aug 14, 2020
Probability-Flow ODE in Infinite-Dimensional Function Spaces
Recent advances in infinite-dimensional diffusion models have demonstrated their effectiveness and scalability in function generation …
Kunwoo Na, Junghyun Lee, Se-Young Yun, Sungbin Lim
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Probability-Flow ODE in Infinite-Dimensional Function Spaces
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
We present a unified likelihood ratio-based confidence sequence (CS) for any (self-concordant) generalized linear model (GLM) that is …
Junghyun Lee, Se-Young Yun, Kwang-Sung Jun
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A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
Logistic bandit is a ubiquitous framework of modeling users’ choices, e.g., click vs. no click for advertisement recommender …
Junghyun Lee, Se-Young Yun, Kwang-Sung Jun
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Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
Deep Learning Theory - Optimization
specific topics tbd
Junghyun Lee
Sample Complexity of Learning in Structured Markov Chains and MDPs
(tbd)
Junghyun Lee
Theoretical Analyses of Reinforcement Learning with Human Feedback (RLHF) and Related Problems
(tbd)
Junghyun Lee