Learning from failure: De-biasing classifier from biased classifier J Nam, H Cha, SS Ahn, J Lee, J Shin Neural Information Processing Systems (NeurIPS), 2020 | 337 | 2020 |
CoL: Contrastive continual learning H Cha, J Lee, J Shin International Conference on Computer Vision (ICCV), 2021 | 258 | 2021 |
Minimax statistical learning with Wasserstein distances J Lee, M Raginsky Neural Information Processing Systems (NeurIPS), 2018 | 193 | 2018 |
Layer-adaptive sparsity for the magnitude-based pruning J Lee, S Park, S Mo, S Ahn, J Shin International Conference on Learning Representations (ICLR), 2021 | 119 | 2021 |
Minimum width for universal approximation S Park, C Yun, J Lee, J Shin International Conference on Learning Representations (ICLR), 2021 | 119 | 2021 |
Lookahead: A far-sighted alternative of magnitude-based pruning S Park*, J Lee*, S Mo, J Shin International Conference on Learning Representations (ICLR), 2020 | 99 | 2020 |
Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation J Nam, J Kim, J Lee, J Shin International Conference on Learning Representations (ICLR), 2022 | 47 | 2022 |
Learning bounds for risk-sensitive learning J Lee, S Park, J Shin Neural Information Processing Systems (NeurIPS), 2020 | 45 | 2020 |
MASKER: Masked keyword regularization for reliable text classification SJ Moon, S Mo, K Lee, J Lee, J Shin AAAI Conference on Artificial Intelligence (AAAI), 2021 | 32 | 2021 |
Provable memorization via deep neural networks using sub-linear parameters S Park, J Lee, C Yun, J Shin Conference on Learning Theory (COLT), 2021 | 30 | 2021 |
Scalable Neural Video Representations with Learnable Positional Features S Kim, S Yu, J Lee, J Shin Neural Information Processing Systems (NeurIPS), 2022 | 23 | 2022 |
Meta-Learning sparse implicit neural representations J Lee*, J Tack*, N Lee, J Shin Neural Information Processing Systems (NeurIPS), 2021 | 22 | 2021 |
Explaining Visual Biases as Words by Generating Captions Y Kim, S Mo, M Kim, K Lee, J Lee, J Shin arXiv preprint arXiv:2301.11104, 2023 | 17* | 2023 |
Learning finite-dimensional coding schemes with nonlinear reconstruction maps J Lee, M Raginsky SIAM Journal on Mathematics of Data Science (SIMODS), 2019 | 13 | 2019 |
Modality-Agnostic Variational Compression of Implicit Neural Representations JR Schwarz, J Tack, YW Teh, J Lee, J Shin International Conference on Machine Learning (ICML), 2023 | 11 | 2023 |
Zero-shot Blind Image Denoising via Implicit Neural Representations C Kim, J Lee, J Shin arXiv preprint arXiv:2204.02405, 2022 | 10 | 2022 |
Meta-Learning with Self-Improving Momentum Target J Tack, J Park, H Lee, J Lee, J Shin Neural Information Processing Systems (NeurIPS), 2022 | 6 | 2022 |
MaskedKD: Efficient Distillation of Vision Transformers with Masked Images S Son, N Lee, J Lee arXiv preprint arXiv:2302.10494, 2023 | 4 | 2023 |
Learning Large-scale Neural Fields via Context Pruned Meta-Learning J Tack, S Kim, S Yu, J Lee, J Shin, JR Schwarz Neural Information Processing Systems (NeurIPS), 2023 | 4* | 2023 |
Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling J Nam, S Mo, J Lee, J Shin arXiv preprint arXiv:2212.02090, 2022 | 3 | 2022 |