convex function
Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima
To address this gap, we study deterministic/stochastic versions of SAM with practical configurations (i.e., constant
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Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling
Zheng Qu, Peter Richtarik, Tong Zhang
Neural Information Processing Systems http://nips.cc/
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A Unified Framework for Rank-based Loss Minimization
The empirical risk function is the cornerstone of machine learning.
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