3 papers
math.OC2026
Stochastic Trust-Region Methods for Over-parameterized Models
Aike Yang, Hao Wang
Under interpolation-type assumptions such as the strong growth condition, stochastic optimization methods can attain convergence rates comparable to full-batch methods, but their p…
math.OC2026
Regularization for Sparse Optimization: Consistency and Global Convergence
Yaohua Hu, Hao Wang, Xiaoqi Yang
The regularization method has a strong sparsity promoting capability in approaching sparse solutions of linear inverse problems and gained successful applicatio…
math.OC2025
Alternating Iteratively Reweighted and Subspace Newton Algorithms for Nonconvex Sparse Optimization
Hao Wang, Xiangyu Yang, Yichen Zhu
This paper presents a novel hybrid algorithm for minimizing the sum of a continuously differentiable loss function and a nonsmooth, possibly nonconvex, sparse regularization functi…