Jaeho Lee
Jaeho Lee
Postdoctoral researcher at KAIST
Verified email at kaist.ac.kr - Homepage
Title
Cited by
Cited by
Year
Minimax statistical learning with Wasserstein distances
J Lee, M Raginsky
Advances in Neural Information Processing Systems 31, 2687-2696, 2018
80*2018
Minimum width for universal approximation
S Park, C Yun, J Lee, J Shin
International Conference on Learning Representations (ICLR), 2021
172021
Lookahead: A far-sighted alternative of magnitude-based pruning
S Park*, J Lee*, S Mo, J Shin
International Conference on Learning Representations (ICLR), 2020
162020
Learning from failure: De-biasing classifier from biased classifier
J Nam, H Cha, SS Ahn, J Lee, J Shin
Advances in Neural Information Processing Systems 33, 2020
8*2020
Learning bounds for risk-sensitive learning
J Lee, S Park, J Shin
Advances in Neural Information Processing Systems 33, 2020
82020
Learning finite-dimensional coding schemes with nonlinear reconstruction maps
J Lee, M Raginsky
SIAM Journal on Mathematics of Data Science 1 (3), 617-642, 2019
52019
Layer-adaptive sparsity for the bagnitude-based pruning
J Lee, S Park, S Mo, S Ahn, J Shin
International Conference on Learning Representations (ICLR), 2021
1*2021
MASKER: Masked Keyword Regularization for Reliable Text Classification
SJ Moon, S Mo, K Lee, J Lee, J Shin
AAAI, 2021
2021
Provable Memorization via Deep Neural Networks using Sub-linear Parameters
S Park, J Lee, C Yun, J Shin
arXiv preprint arXiv:2010.13363, 2020
2020
Robustness and generalization guarantees for statistical learning of generative models
J Lee
University of Illinois at Urbana-Champaign, 2019
2019
On MMSE estimation from quantized observations in the nonasymptotic regime
J Lee, M Raginsky, P Moulin
2015 IEEE International Symposium on Information Theory (ISIT), 2924-2928, 2015
2015
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Articles 1–11