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cs.LG2026
Mild Over-Parameterization Benefits Asymmetric Tensor PCA
Shihong Ding, Weicheng Lin, Cong Fang
Asymmetric Tensor PCA (ATPCA) is a prototypical model for studying the trade-offs between sample complexity, computation, and memory. Existing algorithms for this problem typically…
cs.LG2024
An Effective Dynamic Gradient Calibration Method for Continual Learning
Weichen Lin, Jiaxiang Chen, Ruomin Huang +1
Continual learning (CL) is a fundamental topic in machine learning, where the goal is to train a model with continuously incoming data and tasks. Due to the memory limit, we cannot…