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math.OC2026
Low-Order Explicit Hessian Imitation Method for Large-Scale Supervised Machine Learning
Yunlang Zhu, Lingjun Guo, Zahra Khatti +4
An algorithm is proposed for solving optimization problems arising in neural network training for supervised learning. The unique feature of the algorithm is the use of an auxiliar…
math.OC2026
A Proximal-Gradient Method for Solving Regularized Optimization Problems with General Constraints
Frank E. Curtis, Xiaoyi Qu, Daniel P. Robinson
We propose, analyze, and test a proximal-gradient method for solving regularized optimization problems with general constraints. The method employs a decomposition strategy to comp…
math.OC2024
A Proximal-Gradient Method for Constrained Optimization
Yutong Dai, Xiaoyi Qu, Daniel P. Robinson
We present a new algorithm for solving optimization problems with objective functions that are the sum of a smooth function and a (potentially) nonsmooth regularization function, a…