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Scaling Laws of SignSGD in Linear Regression: When Does It Outperform SGD?
Jihwan Kim, Dogyoon Song, Chulhee Yun
Minor First, Major Last: A Depth-Induced Implicit Bias of Sharpness-Aware Minimization
Chaewon Moon, Dongkuk Si, Chulhee Yun
Implicit Bias of Per-sample Adam on Separable Data: Departure from the Full-batch Regime
Beomhan Baek, Minhak Song, Chulhee Yun
Implicit Bias and Loss of Plasticity in Matrix Completion: Depth Promotes Low-Rankness
Baekrok Shin, Chulhee Yun
Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training
Minhak Song, Beomhan Baek, Kwangjun Ahn, Chulhee Yun
Provable Benefit of Random Permutations over Uniform Sampling in Stochastic Coordinate Descent
Donghwa Kim, Jaewook Lee, Chulhee Yun
Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More
Geonhui Yoo, Minhak Song, Chulhee Yun
Incremental Gradient Descent with Small Epoch Counts is Surprisingly Slow on Ill-Conditioned Problems
Yujun Kim, Jaeyoung Cha, Chulhee Yun
Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
Yeseul Cho, Baekrok Shin, Changmin Kang, Chulhee Yun
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
Hyunji Jung, Hanseul Cho, Chulhee Yun