Chulhee Yun - RankMe

85 papers A* 34Misc 1Journal 44Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Implicit Bias and Loss of Plasticity in Matrix Completion: Depth Promotes Low-Rankness. CoRR Baekrok Shin, Chulhee Yun
2026	J	`jnl`	Minor First, Major Last: A Depth-Induced Implicit Bias of Sharpness-Aware Minimization. CoRR Chaewon Moon, Dongkuk Si, Chulhee Yun
2026	J	`jnl`	Regularized Online RLHF with Generalized Bilinear Preferences. CoRR Junghyun Lee, Minju Hong, Kwang-Sung Jun, Chulhee Yun, Se-Young Yun
2026	J	`jnl`	Scaling Laws of SignSGD in Linear Regression: When Does It Outperform SGD? CoRR Jihwan Kim, Dogyoon Song, Chulhee Yun
2026	J	`jnl`	Uniform Spectral Growth and Convergence of Muon in LoRA-Style Matrix Factorization. CoRR Changmin Kang, Jihun Yun, Baekrok Shin, Yeseul Cho, Chulhee Yun
2025	A*	`conf`	Arithmetic Transformers Can Length-Generalize in Both Operand Length and Count. ICLR Hanseul Cho, Jaeyoung Cha, Srinadh Bhojanapalli, Chulhee Yun
2025	A*	`conf`	Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification. ICLR Hyunji Jung, Hanseul Cho, Chulhee Yun
2025	J	`jnl`	Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification. CoRR Hyunji Jung, Hanseul Cho, Chulhee Yun
2025	A*	`conf`	Does SGD really happen in tiny subspaces? ICLR Minhak Song, Kwangjun Ahn, Chulhee Yun
2025	J	`jnl`	From Linear to Nonlinear: Provable Weak-to-Strong Generalization through Feature Learning. CoRR Junsoo Oh, Jerry Song, Chulhee Yun
2025	J	`jnl`	Implicit Bias of Per-sample Adam on Separable Data: Departure from the Full-batch Regime. CoRR Beomhan Baek, Minhak Song, Chulhee Yun
2025	A*	`conf`	Incremental Gradient Descent with Small Epoch Counts is Surprisingly Slow on Ill-Conditioned Problems. ICML Yujun Kim, Jaeyoung Cha, Chulhee Yun
2025	J	`jnl`	Incremental Gradient Descent with Small Epoch Counts is Surprisingly Slow on Ill-Conditioned Problems. CoRR Yujun Kim, Jaeyoung Cha, Chulhee Yun
2025	A*	`conf`	Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty. ICML Yeseul Cho, Baekrok Shin, Changmin Kang, Chulhee Yun
2025	J	`jnl`	Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty. CoRR Yeseul Cho, Baekrok Shin, Changmin Kang, Chulhee Yun
2025	A*	`conf`	Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo. ICLR Hyunsu Kim, Giung Nam, Chulhee Yun, Hongseok Yang, Juho Lee
2025	J	`jnl`	Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo. CoRR Hyunsu Kim, Giung Nam, Chulhee Yun, Hongseok Yang, Juho Lee
2025	A*	`conf`	Provable Benefit of Random Permutations over Uniform Sampling in Stochastic Coordinate Descent. ICML Donghwa Kim, Jaewook Lee, Chulhee Yun
2025	J	`jnl`	Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements. CoRR Jiseok Chae, Chulhee Yun, Donghwan Kim
2025	J	`jnl`	The Cost of Robustness: Tighter Bounds on Parameter Complexity for Robust Memorization in ReLU Nets. CoRR Yujun Kim, Chaewon Moon, Chulhee Yun
2025	J	`jnl`	Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training. CoRR Minhak Song, Beomhan Baek, Kwangjun Ahn, Chulhee Yun
2025	A*	`conf`	Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More. ICML Geonhui Yoo, Minhak Song, Chulhee Yun
2025	J	`jnl`	Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More. CoRR Geonhui Yoo, Minhak Song, Chulhee Yun
2024	J	`jnl`	Arithmetic Transformers Can Length-Generalize in Both Operand Length and Count. CoRR Hanseul Cho, Jaeyoung Cha, Srinadh Bhojanapalli, Chulhee Yun
2024	A*	`conf`	DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity. NeurIPS Baekrok Shin, Junsoo Oh, Hanseul Cho, Chulhee Yun
2024	J	`jnl`	DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity. CoRR Baekrok Shin, Junsoo Oh, Hanseul Cho, Chulhee Yun
2024	J	`jnl`	Does SGD really happen in tiny subspaces? CoRR Minhak Song, Kwangjun Ahn, Chulhee Yun
2024	A*	`conf`	Fundamental Benefit of Alternating Updates in Minimax Optimization. ICML Jaewook Lee, Hanseul Cho, Chulhee Yun
2024	J	`jnl`	Fundamental Benefit of Alternating Updates in Minimax Optimization. CoRR Jaewook Lee, Hanseul Cho, Chulhee Yun
2024	A*	`conf`	Linear attention is (maybe) all you need (to understand Transformer optimization). ICLR Kwangjun Ahn, Xiang Cheng, Minhak Song, Chulhee Yun, Ali Jadbabaie, Suvrit Sra
2024	A*	`conf`	Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure. NeurIPS Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun
2024	J	`jnl`	Position Coupling: Leveraging Task Structure for Improved Length Generalization of Transformers. CoRR Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun
2024	A*	`conf`	Provable Benefit of Cutout and CutMix for Feature Learning. NeurIPS Junsoo Oh, Chulhee Yun
2024	J	`jnl`	Provable Benefit of Cutout and CutMix for Feature Learning. CoRR Junsoo Oh, Chulhee Yun
2024	A*	`conf`	Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements. NeurIPS Jiseok Chae, Chulhee Yun, Donghwan Kim
2023	J	`jnl`	Enhancing Generalization and Plasticity for Sample Efficient Reinforcement Learning. CoRR Hojoon Lee, Hanseul Cho, Hyunseung Kim, Daehoon Gwak, Joonkee Kim, Jaegul Choo, Se-Young Yun, Chulhee Yun
2023	A*	`conf`	Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. NeurIPS Junghyun Lee, Hanseul Cho, Se-Young Yun, Chulhee Yun
2023	J	`jnl`	Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. CoRR Junghyun Lee, Hanseul Cho, Se-Young Yun, Chulhee Yun
2023	J	`jnl`	Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study. CoRR Prin Phunyaphibarn, Junghyun Lee, Bohan Wang, Huishuai Zhang, Chulhee Yun
2023	J	`jnl`	Linear attention is (maybe) all you need (to understand transformer optimization). CoRR Kwangjun Ahn, Xiang Cheng, Minhak Song, Chulhee Yun, Ali Jadbabaie, Suvrit Sra
2023	A*	`conf`	On the Training Instability of Shuffling SGD with Batch Normalization. ICML David Xing Wu, Chulhee Yun, Suvrit Sra
2023	J	`jnl`	On the Training Instability of Shuffling SGD with Batch Normalization. CoRR David Xing Wu, Chulhee Yun, Suvrit Sra
2023	A*	`conf`	PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning. NeurIPS Hojoon Lee, Hanseul Cho, Hyunseung Kim, Daehoon Gwak, Joonkee Kim, Jaegul Choo, Se-Young Yun, Chulhee Yun
2023	A*	`conf`	Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima. NeurIPS Dongkuk Si, Chulhee Yun
2023	J	`jnl`	Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima. CoRR Dongkuk Si, Chulhee Yun
2023	A*	`conf`	Provable Benefit of Mixup for Finding Optimal Decision Boundaries. ICML Junsoo Oh, Chulhee Yun
2023	J	`jnl`	Provable Benefit of Mixup for Finding Optimal Decision Boundaries. CoRR Junsoo Oh, Chulhee Yun
2023	A*	`conf`	SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization. ICLR Hanseul Cho, Chulhee Yun
2023	A*	`conf`	Tighter Lower Bounds for Shuffling SGD: Random Permutations and Beyond. ICML Jaeyoung Cha, Jaewook Lee, Chulhee Yun
2023	J	`jnl`	Tighter Lower Bounds for Shuffling SGD: Random Permutations and Beyond. CoRR Jaeyoung Cha, Jaewook Lee, Chulhee Yun
2023	A*	`conf`	Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory. NeurIPS Minhak Song, Chulhee Yun
2023	J	`jnl`	Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory. CoRR Minhak Song, Chulhee Yun
2022	A*	`conf`	Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond. ICLR Chulhee Yun, Shashank Rajput, Suvrit Sra
2022	J	`jnl`	SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization. CoRR Hanseul Cho, Chulhee Yun
2021	A*	`conf`	A unifying view on implicit bias in training linear neural networks. ICLR Chulhee Yun, Shankar Krishnan, Hossein Mobahi
2021	J	`jnl`	Can Single-Shuffle SGD be Better than Reshuffling SGD and GD? CoRR Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2021	J	`jnl`	Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond. CoRR Chulhee Yun, Shashank Rajput, Suvrit Sra
2021	A*	`conf`	Minimum Width for Universal Approximation. ICLR Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin
2021	A*	`conf`	Open Problem: Can Single-Shuffle SGD be Better than Reshuffling SGD and GD? COLT Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2021	—	`—`	Optimization for Deep Learning: Bridging the Theory-Practice Gap. Chulhee Yun
2021	A*	`conf`	Provable Memorization via Deep Neural Networks using Sub-linear Parameters. COLT Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin
2020	J	`jnl`	$O(n)$ Connections are Expressive Enough: Universal Approximability of Sparse Transformers. CoRR Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	J	`jnl`	A Unifying View on Implicit Bias in Training Linear Neural Networks. CoRR Chulhee Yun, Shankar Krishnan, Hossein Mobahi
2020	A*	`conf`	Are Transformers universal approximators of sequence-to-sequence functions? ICLR Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	A*	`conf`	Low-Rank Bottleneck in Multi-head Attention Models. ICML Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	J	`jnl`	Low-Rank Bottleneck in Multi-head Attention Models. CoRR Srinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	J	`jnl`	Minimum Width for Universal Approximation. CoRR Sejun Park, Chulhee Yun, Jaeho Lee, Jinwoo Shin
2020	A*	`conf`	O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers. NeurIPS Chulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2020	J	`jnl`	Provable Memorization via Deep Neural Networks using Sub-linear Parameters. CoRR Sejun Park, Jaeho Lee, Chulhee Yun, Jinwoo Shin
2020	A*	`conf`	SGD with shuffling: optimal rates without component convexity and large epoch requirements. NeurIPS Kwangjun Ahn, Chulhee Yun, Suvrit Sra
2019	J	`jnl`	Are Transformers universal approximators of sequence-to-sequence functions? CoRR Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar
2019	A*	`conf`	Are deep ResNets provably better than linear predictors? NeurIPS Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2019	J	`jnl`	Are deep ResNets provably better than linear predictors? CoRR Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2019	—	`conf`	Efficiently testing local optimality and escaping saddles for ReLU networks. ICLR (Poster) Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2019	A*	`conf`	Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity. NeurIPS Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2019	—	`conf`	Small nonlinearities in activation functions create bad local minima in neural networks. ICLR (Poster) Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2018	J	`jnl`	A Critical View of Global Optimality in Deep Learning. CoRR Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2018	J	`jnl`	Efficiently testing local optimality and escaping saddles for ReLU networks. CoRR Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2018	J	`jnl`	Finite sample expressive power of small-width ReLU networks. CoRR Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2018	—	`conf`	Global Optimality Conditions for Deep Neural Networks. ICLR (Poster) Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2018	A*	`conf`	Minimax Bounds on Stochastic Batched Convex Optimization. COLT John C. Duchi, Feng Ruan, Chulhee Yun
2017	J	`jnl`	Global optimality conditions for deep neural networks. CoRR Chulhee Yun, Suvrit Sra, Ali Jadbabaie
2015	Misc	`conf`	Face detection using Local Hybrid Patterns. ICASSP Chulhee Yun, Donghoon Lee, Chang Dong Yoo
2013	—	`conf`	A fusion of computer vision technique and a visual programming language for edutainment robots. ISR Chulhee Yun, Jaegon Ahn, Yeon-Ho Kim
2013	—	`conf`	An implementation of computer vision technique for an edutainment robot with a visual programming language. URAI Chulhee Yun, Jaegon Ahn, Yeon-Ho Kim