2 citations · 2 across the 6 of their papers we have counts for
6 papers
Learning-rate-free Momentum SGD with Reshuffling Converges in Nonsmooth Nonconvex Optimization
Xiaoyin Hu, Nachuan Xiao, Xin Liu +1
In this paper, we propose a generalized framework for developing learning-rate-free momentum stochastic gradient descent (SGD) methods in the minimization of nonsmooth nonconvex fu…
Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization
Nachuan Xiao, Kuangyu Ding, Xiaoyin Hu +1
In this paper, we consider the minimization of a nonsmooth nonconvex objective function over a closed convex subset of , with additional nonsmoot…
An Inexact Preconditioned Zeroth-order Proximal Method for Composite Optimization
Shanglin Liu, Lei Wang, Nachuan Xiao +1
In this paper, we consider the composite optimization problem, where the objective function integrates a continuously differentiable loss function with a nonsmooth regularization t…
Adam-family Methods with Decoupled Weight Decay in Deep Learning
Kuangyu Ding, Nachuan Xiao, Kim-Chuan Toh
In this paper, we investigate the convergence properties of a wide class of Adam-family methods for minimizing quadratically regularized nonsmooth nonconvex optimization problems,…
A Riemannian Dimension-reduced Second Order Method with Application in Sensor Network Localization
Tianyun Tang, Kim-Chuan Toh, Nachuan Xiao +1
In this paper, we propose a cubic-regularized Riemannian optimization method (RDRSOM), which partially exploits the second order information and achieves the iteration complexity o…
A Partial Exact Penalty Function Approach for Constrained Optimization
Nachuan Xiao, Xin Liu, Kim-Chuan Toh
In this paper, we focus on a class of constrained nonlinear optimization problems (NLP), where some of its equality constraints define a closed embedded submanifold i…