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2020 – today
- 2021
[c17]Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin:
Provable Memorization via Deep Neural Networks using Sub-linear Parameters. COLT 2021: 3627-3661- [c16]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Open Problem: Can Single-Shuffle SGD be Better than Reshuffling SGD and GD? COLT 2021: 4653-4658 - [c15]Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin:
Minimum Width for Universal Approximation. ICLR 2021 - [c14]Chulhee Yun, Shankar Krishnan, Hossein Mobahi:
A unifying view on implicit bias in training linear neural networks. ICLR 2021 - [i12]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Can Single-Shuffle SGD be Better than Reshuffling SGD and GD? CoRR abs/2103.07079 (2021) - 2020
- [c13]Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar:
Are Transformers universal approximators of sequence-to-sequence functions? ICLR 2020 - [c12]Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar:
Low-Rank Bottleneck in Multi-head Attention Models. ICML 2020: 864-873 - [c11]Kwangjun Ahn, Chulhee Yun, Suvrit Sra:
SGD with shuffling: optimal rates without component convexity and large epoch requirements. NeurIPS 2020 - [c10]Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar:
O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers. NeurIPS 2020 - [i11]Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar:
Low-Rank Bottleneck in Multi-head Attention Models. CoRR abs/2002.07028 (2020) - [i10]Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar:
$O(n)$ Connections are Expressive Enough: Universal Approximability of Sparse Transformers. CoRR abs/2006.04862 (2020) - [i9]Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin:
Minimum Width for Universal Approximation. CoRR abs/2006.08859 (2020) - [i8]Chulhee Yun, Shankar Krishnan, Hossein Mobahi:
A Unifying View on Implicit Bias in Training Linear Neural Networks. CoRR abs/2010.02501 (2020) - [i7]Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin:
Provable Memorization via Deep Neural Networks using Sub-linear Parameters. CoRR abs/2010.13363 (2020)
2010 – 2019
- 2019
- [c9]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Efficiently testing local optimality and escaping saddles for ReLU networks. ICLR (Poster) 2019 - [c8]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Small nonlinearities in activation functions create bad local minima in neural networks. ICLR (Poster) 2019 - [c7]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity. NeurIPS 2019: 15532-15543 - [c6]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Are deep ResNets provably better than linear predictors? NeurIPS 2019: 15660-15669 - [i6]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Are deep ResNets provably better than linear predictors? CoRR abs/1907.03922 (2019) - [i5]Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar:
Are Transformers universal approximators of sequence-to-sequence functions? CoRR abs/1912.10077 (2019) - 2018
- [c5]John C. Duchi, Feng Ruan, Chulhee Yun:
Minimax Bounds on Stochastic Batched Convex Optimization. COLT 2018: 3065-3162 - [c4]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Global Optimality Conditions for Deep Neural Networks. ICLR (Poster) 2018 - [i4]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
A Critical View of Global Optimality in Deep Learning. CoRR abs/1802.03487 (2018) - [i3]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Efficiently testing local optimality and escaping saddles for ReLU networks. CoRR abs/1809.10858 (2018) - [i2]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Finite sample expressive power of small-width ReLU networks. CoRR abs/1810.07770 (2018) - 2017
- [i1]Chulhee Yun, Suvrit Sra, Ali Jadbabaie:
Global optimality conditions for deep neural networks. CoRR abs/1707.02444 (2017) - 2015
- [c3]Chulhee Yun, Donghoon Lee, Chang Dong Yoo:
Face detection using Local Hybrid Patterns. ICASSP 2015: 1468-1472 - 2013
- [c2]Chulhee Yun, Jaegon Ahn, Yeon-Ho Kim:
A fusion of computer vision technique and a visual programming language for edutainment robots. ISR 2013: 1-5 - [c1]Chulhee Yun, Jaegon Ahn, Yeon-Ho Kim:
An implementation of computer vision technique for an edutainment robot with a visual programming language. URAI 2013: 131-133
Coauthor Index
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