Jaeho Lee

I am a postdoc at the algorithmic intelligence laboratory at KAIST, working with Jinwoo Shin. Before joining here, I completed my Ph.D. under the guidance of Maxim Raginsky, in the middle of the lovely cornfields of Urbana-Champaign. Even prior to this, I was an undergraduate student at KAIST, double-majoring the electrical engineering and the management science.

My research focuses on analyzing the impact of operational constraints on the generalization/approximation capabilities of learning algorithms; the constraints may be about robustness, fairness, risk-sensitivity, or sparsity. As a research tool, I like to use the machineries from the statistical learning theory (all hail Vapnik!), high-dimensional statistics, and computational libraries for machine learning.

For any inquiries (or CV), please contact me via email: jaeho-lee [at] kaist [dot] ac [dot] kr. I may respond even faster via Twitter: @jaeho_lee_



publications & preprints

Provable Memorization via Deep Neural Networks using Sub-linear Parameters
Sejun Park, JL, Chulhee Yun, and Jinwoo Shin
Preprint, 2020.

Minimal width for universal approximation
Sejun Park, Chulhee Yun, JL, and Jinwoo Shin
Preprint, 2020.
(Sejun will give a 20-min presentation at Deepmath 2020!)

A deeper look at the layerwise sparsity of magnitude-based pruning
JL, Sejun Park, Sangwoo Mo, Sungsoo Ahn, and Jinwoo Shin
Preprint, 2020.

Learning bounds for risk-sensitive learning
JL, Sejun Park, and Jinwoo Shin
NeurIPS 2020. [code, slide]

Learning from failure: Training debiased classifier from biased classifier
Junhyun Nam, Hyuntak Cha, Sungsoo Ahn, JL, and Jinwoo Shin
NeurIPS 2020.

Lookahead: A far-sighted alternative of magnitude-based pruning
{Sejun Park, JL}equal, Sangwoo Mo, and Jinwoo Shin
ICLR 2020.

Learning finite-dimensional coding schemes with nonlinear reconstruction maps
JL and Maxim Raginsky
SIMODS 2019.

Minimax statistical learning with Wasserstein distances
JL and Maxim Raginsky
NeurIPS 2018.
[video]

On MMSE estimation from quantized observations in the nonasymptotic regime
JL, Maxim Raginsky, and Pierre Moulin
ISIT 2015.



teaching



invited talks



awards & honors



refereeing



miscellaneous



(last updated: October 16, 2020.)