On MMSE estimation from quantized observations in the nonasymptotic regime. - Jaeho Lee 001; Maxim Raginsky; Pierre Moulin (ISIT, 2015)

Minimax Statistical Learning and Domain Adaptation with Wasserstein Distances. - Jaeho Lee 001; Maxim Raginsky (CoRR, 2017)

Minimax Statistical Learning with Wasserstein distances. - Jaeho Lee 001; Maxim Raginsky (NeurIPS, 2018)

Learning Finite-Dimensional Coding Schemes with Nonlinear Reconstruction Maps. - Jaeho Lee 001; Maxim Raginsky (SIAM J. Math. Data Sci., 2019)

Robustness and generalization guarantees for statistical learning of generative models - Jaeho Lee 001 (2019)

Lookahead: A Far-sighted Alternative of Magnitude-based Pruning. - Sejun Park; Jaeho Lee 001; Sangwoo Mo; Jinwoo Shin (ICLR, 2020)

Learning Bounds for Risk-sensitive Learning. - Jaeho Lee 001; Sejun Park; Jinwoo Shin (NeurIPS, 2020)

Learning from Failure: De-biasing Classifier from Biased Classifier. - Jun Hyun Nam; Hyuntak Cha; Sungsoo Ahn; Jaeho Lee 001; Jinwoo Shin (NeurIPS, 2020)

Learning from Failure: Training Debiased Classifier from Biased Classifier. - Jun Hyun Nam; Hyuntak Cha; Sungsoo Ahn; Jaeho Lee 001; Jinwoo Shin (CoRR, 2020)

A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning. - Jaeho Lee 001; Sejun Park; Sangwoo Mo; Sungsoo Ahn; Jinwoo Shin (CoRR, 2020)

MASKER: Masked Keyword Regularization for Reliable Text Classification. - Seung Jun Moon; Sangwoo Mo; Kimin Lee; Jaeho Lee 001; Jinwoo Shin (AAAI, 2021)

Provable Memorization via Deep Neural Networks using Sub-linear Parameters. - Sejun Park; Jaeho Lee 001; Chulhee Yun; Jinwoo Shin (COLT, 2021)

Co2L: Contrastive Continual Learning. - Hyuntak Cha; Jaeho Lee 001; Jinwoo Shin (ICCV, 2021)

Layer-adaptive Sparsity for the Magnitude-based Pruning. - Jaeho Lee 001; Sejun Park; Sangwoo Mo; Sungsoo Ahn; Jinwoo Shin (ICLR, 2021)

Minimum Width for Universal Approximation. - Sejun Park; Chulhee Yun; Jaeho Lee 001; Jinwoo Shin (ICLR, 2021)

Meta-Learning Sparse Implicit Neural Representations. - Jaeho Lee 001; Jihoon Tack; Namhoon Lee; Jinwoo Shin (NeurIPS, 2021)

Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation. - Jun Hyun Nam; Jaehyung Kim 001; Jaeho Lee 001; Jinwoo Shin (ICLR, 2022)

Scalable Neural Video Representations with Learnable Positional Features. - Subin Kim 001; Sihyun Yu; Jaeho Lee 001; Jinwoo Shin (NeurIPS, 2022)

Meta-Learning with Self-Improving Momentum Target. - Jihoon Tack; Jongjin Park; Hankook Lee; Jaeho Lee 001; Jinwoo Shin (NeurIPS, 2022)

Zero-shot Blind Image Denoising via Implicit Neural Representations. - Chaewon Kim; Jaeho Lee 001; Jinwoo Shin (CoRR, 2022)

Modality-Agnostic Variational Compression of Implicit Neural Representations. - Jonathan Richard Schwarz; Jihoon Tack; Yee Whye Teh; Jaeho Lee 001; Jinwoo Shin (ICML, 2023)

Learning Large-scale Neural Fields via Context Pruned Meta-Learning. - Jihoon Tack; Subin Kim 001; Sihyun Yu; Jaeho Lee 001; Jinwoo Shin; Jonathan Richard Schwarz (NeurIPS, 2023)

Semi-Ensemble: A Simple Approach Over-parameterize Model Interpolation. - Jiwoon Lee; Jaeho Lee 001 (UniReps, 2023)

Explaining Visual Biases as Words by Generating Captions. - Younghyun Kim; Sangwoo Mo; Minkyu Kim 004; Kyungmin Lee; Jaeho Lee 001; Jinwoo Shin (CoRR, 2023)

Efficient Meta-Learning via Error-based Context Pruning for Implicit Neural Representations. - Jihoon Tack; Subin Kim 001; Sihyun Yu; Jaeho Lee 001; Jinwoo Shin; Jonathan Richard Schwarz (CoRR, 2023)

MaskedKD: Efficient Distillation of Vision Transformers with Masked Images. - Seungwoo Son 005; Namhoon Lee; Jaeho Lee 001 (CoRR, 2023)

Debiased Distillation by Transplanting the Last Layer. - Jiwoon Lee; Jaeho Lee 001 (CoRR, 2023)

Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling. - Junhyun Nam; Sangwoo Mo; Jaeho Lee 001; Jinwoo Shin (Trans. Mach. Learn. Res., 2023)

Discovering and Mitigating Visual Biases Through Keyword Explanation. - Younghyun Kim; Sangwoo Mo; Minkyu Kim 004; Kyungmin Lee; Jaeho Lee 001; Jinwoo Shin (CVPR, 2024)

In Search of a Data Transformation that Accelerates Neural Field Training. - Junwon Seo; Sangyoon Lee; Kwang In Kim; Jaeho Lee 001 (CVPR, 2024)

The Role of Masking for Efficient Supervised Knowledge Distillation of Vision Transformers. - Seungwoo Son 005; Jegwang Ryu; Namhoon Lee; Jaeho Lee 001 (ECCV (67), 2024)

Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization. - Sungbin Shin; Wonpyo Park; Jaeho Lee 001; Namhoon Lee (EMNLP, 2024)

Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization. - Seungwoo Son 005; Wonpyo Park; Woohyun Han; Kyuyeun Kim; Jaeho Lee 001 (EMNLP, 2024)

Hybrid Neural Representations for Spherical Data. - Hyomin Kim; Yunhui Jang; Jaeho Lee 001; Sungsoo Ahn (ICML, 2024)

Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity. - Hagyeong Lee; Minkyu Kim 004; Jun-Hyuk Kim; Seungeon Kim; Dokwan Oh; Jaeho Lee 001 (ICML, 2024)

SCANNER: Knowledge-Enhanced Approach for Robust Multi-modal Named Entity Recognition of Unseen Entities. - Hyunjong Ok; Taeho Kil; Sukmin Seo; Jaeho Lee 001 (NAACL-HLT, 2024)

Attention-Aware Semantic Communications for Collaborative Inference. - Jiwoong Im; Nayoung Kwon; Taewoo Park; Jiheon Woo; Jaeho Lee 001; Yongjune Kim 001 (IEEE Internet Things J., 2024)

ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models. - Seonghwan Park; Jaehyeon Jeong; Yongjun Kim; Jaeho Lee 001; Namhoon Lee (ICLR, 2025)

Communication-Efficient Split Learning via Adaptive Feature-Wise Compression. - Yongjeong Oh; Jaeho Lee 001; Christopher G. Brinton; Yo-Seb Jeon (IEEE Trans. Neural Networks Learn. Syst., 2025)