Chulhee Yun

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Suvrit SraTU Munich / MITVerified email at mit.edu
Ali JadbabaieJR East Professor of Engineering, MITVerified email at mit.edu
Ankit Singh RawatResearch Scientist, GoogleVerified email at google.com
Sashank J. ReddiResearch Scientist, Google ResearchVerified email at cs.cmu.edu
Srinadh BhojanapalliResearch Scientist, Google ResearchVerified email at google.com
Sanjiv KumarGoogle Fellow, VP, Google ResearchVerified email at google.com
Jaeho LeePOSTECHVerified email at postech.ac.kr
Jinwoo ShinKAIST Endowed Chair ProfessorVerified email at kaist.ac.kr
Kwangjun AhnPhD Student, MITVerified email at mit.edu
Yin-Wen ChangGoogle Inc.Verified email at google.com
Hossein MobahiResearch Scientist @ GoogleVerified email at csail.mit.edu
Shankar KrishnanGoogle ResearchVerified email at google.com
Shashank RajputResearch Scientist, MosaicML (Databricks)Verified email at databricks.com
Feng RuanDepartment of EECS, University of California, BerkeleyVerified email at berkeley.edu
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityVerified email at stanford.edu
Jaewook LeeMS Student, KAIST AI (OptiML Lab)Verified email at kaist.ac.kr
Jaeyoung ChaMS student, KAIST AIVerified email at kaist.ac.kr
David X WuUniversity of California, Berkeley; Massachusetts Institute of TechnologyVerified email at berkeley.edu
Junsoo OhMaster's student, KAIST AIVerified email at kaist.ac.kr
Dongkuk SiMaster's student, KAISTVerified email at kaist.ac.kr

Chulhee Yun

Assistant Professor, KAIST Kim Jaechul Graduate School of AI

Verified email at kaist.ac.kr - Homepage

optimization deep learning


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Are Transformers universal approximators of sequence-to-sequence functions? C Yun, S Bhojanapalli, AS Rawat, SJ Reddi, S Kumar ICLR 2020 (arXiv:1912.10077), 2019	195	2019
Small nonlinearities in activation functions create bad local minima in neural networks C Yun, S Sra, A Jadbabaie ICLR 2019 (arXiv:1802.03487), 2018	115*	2018
Global optimality conditions for deep neural networks C Yun, S Sra, A Jadbabaie ICLR 2018 (arXiv:1707.02444), 2017	114	2017
Minimum width for universal approximation S Park, C Yun, J Lee, J Shin ICLR 2021 (arXiv:2006.08859), 2020	102	2020
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity C Yun, S Sra, A Jadbabaie NeurIPS 2019 (arXiv:1810.07770), 2019	97	2019
A Unifying View on Implicit Bias in Training Linear Neural Networks C Yun, S Krishnan, H Mobahi ICLR 2021 (arXiv:2010.02501), 2020	64	2020
Low-Rank Bottleneck in Multi-head Attention Models S Bhojanapalli, C Yun, AS Rawat, SJ Reddi, S Kumar ICML 2020 (arXiv:2002.07028), 2020	57	2020
SGD with shuffling: optimal rates without component convexity and large epoch requirements K Ahn, C Yun, S Sra NeurIPS 2020 (arXiv:2006.06946), 2020	50	2020
Connections are Expressive Enough: Universal Approximability of Sparse Transformers C Yun, YW Chang, S Bhojanapalli, AS Rawat, SJ Reddi, S Kumar NeurIPS 2020 (arXiv:2006.04862), 2020	48	2020
Minibatch vs local SGD with shuffling: Tight convergence bounds and beyond C Yun, S Rajput, S Sra ICLR 2022 (arXiv:2110.10342), 2021	29	2021
Minimax bounds on stochastic batched convex optimization J Duchi, F Ruan, C Yun Conference On Learning Theory, 3065-3162, 2018	28	2018
Provable memorization via deep neural networks using sub-linear parameters S Park, J Lee, C Yun, J Shin COLT 2021 (arXiv:2010.13363), 2021	26	2021
Open Problem: Can Single-Shuffle SGD be Better than Reshuffling SGD and GD? C Yun, S Sra, A Jadbabaie COLT 2021 (arXiv:2103.07079), 2021	18*	2021
Are deep ResNets provably better than linear predictors? C Yun, S Sra, A Jadbabaie NeurIPS 2019 (arXiv:1907.03922), 2019	13	2019
Efficiently testing local optimality and escaping saddles for ReLU networks C Yun, S Sra, A Jadbabaie ICLR 2019 (arXiv:1809.10858), 2018	8	2018
Tighter Lower Bounds for Shuffling SGD: Random Permutations and Beyond J Cha, J Lee, C Yun ICML 2023 (arXiv:2303.07160), 2023	7	2023
SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization H Cho, C Yun ICLR 2023 (arXiv:2210.05995), 2022	3	2022
Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory M Song, C Yun NeurIPS 2023 (arXiv:2307.04204), 2023	1	2023
Provable Benefit of Mixup for Finding Optimal Decision Boundaries J Oh, C Yun ICML 2023 (arXiv:2306.00267), 2023	1	2023
On the Training Instability of Shuffling SGD with Batch Normalization DX Wu, C Yun, S Sra ICML 2023 (arXiv:2302.12444), 2023	1	2023

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