6 citations · 6 across the 5 of their papers we have counts for
5 papers
Single-loop stochastic smoothing algorithms for nonsmooth Riemannian optimization
Kangkang Deng, Zheng Peng, Weihe Wu
In this paper, we develop two Riemannian stochastic smoothing algorithms for nonsmooth optimization problems on Riemannian manifolds, addressing distinct forms of the nonsmooth ter…
Inexact Riemannian Gradient Descent Method for Nonconvex Optimization
Juan Zhou, Kangkang Deng, Hongxia Wang +1
Gradient descent methods are fundamental first-order optimization algorithms in both Euclidean spaces and Riemannian manifolds. However, the exact gradient is not readily available…
The Rank-1 Completion Problem for Cubic Tensors
Jinling Zhou, Jiawang Nie, Zheng Peng +1
This paper studies the rank- tensor completion problem for cubic tensors. First of all, we show that this problem is equivalent to a special rank- matrix recovery problem. Wh…
New vector transport operators extending a Riemannian CG algorithm to generalized Stiefel manifold with low-rank applications
Xuejie Wang, Kangkang Deng, Zheng Peng +1
This paper proposes two innovative vector transport operators, leveraging the Cayley transform, for the generalized Stiefel manifold embedded with a non-standard metric. Specifical…
Stochastic Conjugate Frameworks for Nonconvex and Nonsmooth Optimization
Jiangshan Wang, Zheng Peng
We introduce two new stochastic conjugate frameworks for a class of nonconvex and possibly also nonsmooth optimization problems. These frameworks are built upon Stochastic Recursiv…