Publications

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.

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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.

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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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Prin Phunyaphibarn, Junghyun Lee, Bohan Wang, Huishuai Zhang, Chulhee Yun (2023). Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study. In NeurIPS 2023 M3L Workshop (Oral).

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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.

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