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Jung-Hyun Lee
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Publications
- 2024
- [i13]Seong Jin Cho, Gwangsu Kim, Junghyun Lee, Jinwoo Shin, Chang D. Yoo:
Querying Easily Flip-flopped Samples for Deep Active Learning. CoRR abs/2401.09787 (2024) - 2023
- [c72]Yassir Jedra, Junghyun Lee, Alexandre Proutière, Se-Young Yun:
Nearly Optimal Latent State Decoding in Block MDPs. AISTATS 2023: 2805-2904 - [c71]Junghyun Lee, Hanseul Cho, Se-Young Yun, Chulhee Yun:
Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. NeurIPS 2023 - [c70]Junghyun Lee, Laura Schmid, Se-Young Yun:
Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks. OPODIS 2023: 20:1-20:25 - [i12]Junghyun Lee, Laura Schmid, Se-Young Yun:
Communication-Efficient Collaborative Heterogeneous Bandits in Networks. CoRR abs/2303.05445 (2023) - [i10]Junghyun Lee, Se-Young Yun, Kwang-Sung Jun:
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion. CoRR abs/2310.18554 (2023) - [i9]Junghyun Lee, Hanseul Cho, Se-Young Yun, Chulhee Yun:
Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. CoRR abs/2310.18593 (2023) - [i8]Prin Phunyaphibarn, Junghyun Lee, Bohan Wang, Huishuai Zhang, Chulhee Yun:
Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study. CoRR abs/2311.15051 (2023) - 2022
- [c69]Junghyun Lee, Gwangsu Kim, Mahbod Olfat, Mark Hasegawa-Johnson, Chang D. Yoo:
Fast and Efficient MMD-Based Fair PCA via Optimization over Stiefel Manifold. AAAI 2022: 7363-7371 - [i7]Yassir Jedra, Junghyun Lee, Alexandre Proutière, Se-Young Yun:
Nearly Optimal Latent State Decoding in Block MDPs. CoRR abs/2208.08480 (2022) - 2021
- [i4]Junghyun Lee, Gwangsu Kim, Matt Olfat, Mark Hasegawa-Johnson, Chang D. Yoo:
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold. CoRR abs/2109.11196 (2021)
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last updated on 2024-04-25 05:53 CEST by the dblp team
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