Chulhee Yun

Looking Through the Mirror: Minimax-Optimal Regularized Regrets in Online Learning and Bandits
We revisit regularized regret minimization under full-information and bandit feedback, where a learner optimizes an objective of the …
Junghyun Lee, Yujun Kim, Chulhee Yun, Se-Young Yun
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Provably Efficient Regularized Online RLHF with Generalized Bilinear Preferences
We consider the problem of regularized best-response max-regret minimization in online RLHF under general preferences and bandit …
Junghyun Lee, Minju Hong, Kwang-Sung Jun, Chulhee Yun, Se-Young Yun
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Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults
Although gradient descent with Polyak’s momentum is widely used in modern machine and deep learning, a concrete understanding of …
Prin Phunyaphibarn, Junghyun Lee, Bohan Wang, Huishuai Zhang, Chulhee Yun
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Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults
Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint
Proposes a framework for performing fair PCA in memory limited, streaming setting. Sample complexity results and empirical discussions show the superiority of our approach compared to the existing approaches.
Junghyun Lee, Hanseul Cho, Se-Young Yun, Chulhee Yun
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Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint