Publications

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

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

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. In NeurIPS 2025.

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

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. In ICLR 2025, NeurIPS 2024 OWA Workshop.

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

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

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Prin Phunyaphibarn, Junghyun Lee, Bohan Wang, Huishuai Zhang, Chulhee Yun (2024). Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults. In 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. In ICLR 2024.

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

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

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

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Junghyun Lee, Hanseul Cho, Se-Young Yun, Chulhee Yun (2023). Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. In 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. In OPODIS 2023 (best student paper).

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

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

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Junghyun Lee, Minchan Jeong, Namgyu Ho, Se-Young Yun (2022). A Statistical Analysis of Stochastic Gradient Noises for GNNs. In KCC 2022.

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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. In AAAI 2022.

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Junghyun Lee, Chani Jung, Yoo Hwa Park, Dongmin lee, Juyeon Yoon, Shin Yoo (2021). Preliminary Evaluation of SWAY in Permutation Decision Space via a Novel Euclidean Embedding. In SSBSE 2021.

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