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math.OC2026
Direction-Magnitude Decomposition for Low-Rank Matrix Optimization: Faster Convergence and Saddle-to-saddle Dynamics
Yudong Wei, Liang Zhang, Bingcong Li +1
Low-rank matrix optimization is often carried out via the Burer-Monteiro (BM) formulation, but choosing the factorization rank is delicate and can substantially slow optimizati…
math.OC2024
Primal Methods for Variational Inequality Problems with Functional Constraints
Liang Zhang, Niao He, Michael Muehlebach
Variational inequality problems are recognized for their broad applications across various fields including machine learning and operations research. First-order methods have emerg…
math.OC2023
Parameter-Agnostic Optimization under Relaxed Smoothness
Florian Hübler, Junchi Yang, Xiang Li +1
Tuning hyperparameters, such as the stepsize, presents a major challenge of training machine learning models. To address this challenge, numerous adaptive optimization algorithms h…