Publications

2026

Equal contribution

Equal contribution

, Yassir Jedra, Alexandre Proutière, Se-Young Yun (2026). Instance-Optimal Estimation with Multiple LLM Judges on a Budget. arXiv:2605.23362.

Equal contribution

Equal contribution

, Chulhee Yun (2026). Cumulative Distribution Regret Minimization with Max- Quantile Threshold in Multi-Armed Bandit. KCC 2026 (Distinguished Paper Award).

Junghyun Lee, Yujun Kim, Chulhee Yun, Se-Young Yun (2026). Looking Through the Mirror: Minimax-Optimal Regularized Regrets in Online Learning and Bandits. Forthcoming.

Junghyun Lee, Yassir Jedra, Alexandre Proutière, Se-Young Yun (2026). Near-Optimal Clustering in Mixture of Markov Chains. AISTATS 2026.

Junghyun Lee, Kyoungseok Jang, Kwang-Sung Jun, Milan Vojnović, Se-Young Yun (2026). GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression. AISTATS 2026.

Seong Jin Cho, Gwangsu Kim, Junghyun Lee, Hee Suk Yoon, Joshua Tian Jin Tee, Chang D. Yoo (2026). TESSAR: Geometry-Aware Active Regression via Dynamic Voronoi Tessellation. ICLR 2026.

Junghyun Lee, Minju Hong, Kwang-Sung Jun, Chulhee Yun, Se-Young Yun (2026). Provably Efficient Regularized Online RLHF with Generalized Bilinear Preferences. arXiv:2602.23116.

Equal contribution

Equal contribution

, Se-Young Yun (2026). A Jointly Efficient and Optimal Algorithm for Heteroskedastic Generalized Linear Bandits with Adversarial Corruptions. arXiv:2602.10971.

2025

Junghyun Lee, Branislav Kveton, Anup Rao, Subhojyoti Mukherjee, Ryan A. Rossi, Sunav Choudhary, Alexa Siu (2025). Learning to Reason in LLMs by Expectation Maximization. arXiv:2512.20169.

Equal contribution

Equal contribution

, Se-Young Yun (2025). Preliminary Empirical Study of Low-Rank, Hierarchical Gaussian Linear Bandits. KSC 2025.

Woosung Koh, Wonbeen Oh, Jaein Jang, MinHyung Lee, Hyeongjin Kim, Ah Yeon Kim, Joonkee Kim, Junghyun Lee, Taehyeon Kim, Se-Young Yun (2025). AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners. NeurIPS 2025.

Kunwoo Na, Junghyun Lee, Se-Young Yun, Sungbin Lim (2025). Probability-Flow ODE in Infinite-Dimensional Function Spaces. arXiv:2503.10219, ICLR 2025 DeLTa Workshop.

2024

Woosung Koh, Wonbeen Oh, Siyeol Kim, Suhin Shin, Hyeongjin Kim, Jaein Jang, Junghyun Lee, Se-Young Yun (2024). FlickerFusion: Intra-trajectory Domain Generalizing Multi-Agent RL. ICLR 2025, NeurIPS 2024 OWA Workshop.

Kunwoo Na, Junghyun Lee, Se-Young Yun (2024). On the Estimation of Linear Softmax Parametrized Markov Chains. KCC 2024.

Junghyun Lee, Se-Young Yun, Kwang-Sung Jun (2024). A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits. NeurIPS 2024, ICML 2024 ARLET Workshop (Oral).

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Prin Phunyaphibarn

Equal contribution

Equal contribution

, Bohan Wang, Huishuai Zhang, Chulhee Yun (2024). Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults. arXiv:2311.15051, ICML 2024 HiLD Workshop & NeurIPS 2023 M3L Workshop (Oral).

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Seong Jin Cho, Gwangsu Kim, Junghyun Lee, Jinwoo Shin, Chang D. Yoo (2024). Querying Easily Flip-flopped Samples for Deep Active Learning. ICLR 2024.

Junghyun Lee, Se-Young Yun, Kwang-Sung Jun (2024). Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion. AISTATS 2024.

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Junghyun Lee, Se-Young Yun (2024). Empirical Analyses of Corruption in the Clustering of Block MDPs. KTCP 2024.

2023

Equal contribution

, Mohammed Bennabbassi

Equal contribution

, Junghyun Lee, Se-Young Yun (2023). On the Estimation of Linear Softmax Parametrized Probability Distributions. KSC 2023.

Equal contribution

Equal contribution

, Se-Young Yun, Chulhee Yun (2023). Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. NeurIPS 2023.

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Junghyun Lee, Laura Schmid, Se-Young Yun (2023). Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks. OPODIS 2023 (Best Student Paper).

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Equal contribution

Equal contribution

, Alexandre Proutière, Se-Young Yun (2023). Nearly Optimal Latent State Decoding in Block MDPs. AISTATS 2023.

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2022

Junghyun Lee, Se-Young Yun (2022). Preliminary Empirical Analyses of Clustering in Block MDPs. KSC 2022.

Junghyun Lee, Minchan Jeong

Equal contribution

Equal contribution

, Se-Young Yun (2022). A Statistical Analysis of Stochastic Gradient Noises for GNNs. KCC 2022.

Junghyun Lee, Gwangsu Kim, Matt Olfat, Mark Hasegawa-Johnson, Chang D. Yoo (2022). Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold. AAAI 2022.

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2021

Equal contribution

Equal contribution

Equal contribution

Equal contribution

, Juyeon Yoon, Shin Yoo (2021). Preliminary Evaluation of SWAY in Permutation Decision Space via a Novel Euclidean Embedding. SSBSE 2021.

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2016

Junghyun Lee, Minyoung Hwang, Cheolwon Bae (2016). Some Loci in the Animation of a Sangaku Diagram. Forum Geom. 2016.