2 citations · 2 across the 2 of their papers we have counts for
2 papers
math.OC2022
Stochastic Composition Optimization of Functions without Lipschitz Continuous Gradient
Yin Liu, Sam Davanloo Tajbakhsh
In this paper, we study stochastic optimization of two-level composition of functions without Lipschitz continuous gradient. The smoothness property is generalized by the notion of…
math.OC2020★ 2 cited
Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method for Submanifold Optimization
Dewei Zhang, Sam Davanloo Tajbakhsh
We propose a stochastic variance-reduced cubic regularized Newton algorithm to optimize the finite-sum problem over a Riemannian submanifold of the Euclidean space. The proposed al…