12 citations · 29 across the 9 of their papers we have counts for
9 papers
Learning Theory of Distribution Regression with Neural Networks
Zhongjie Shi, Zhan Yu, Ding-Xuan Zhou
In this paper, we aim at establishing an approximation theory and a learning theory of distribution regression via a fully connected neural network (FNN). In contrast to the classi…
Distributed Gradient Descent for Functional Learning
Zhan Yu, Jun Fan, Zhongjie Shi +1
In recent years, different types of distributed and parallel learning schemes have received increasing attention for their strong advantages in handling large-scale data informatio…
Distributed Constrained Optimization with Delayed Subgradient Information over Time-Varying Network under Adaptive Quantization
Jie Liu, Zhan Yu, Daniel W. C. Ho
In this paper, we consider a distributed constrained optimization problem with delayed subgradient information over the time-varying communication network, where each agent can onl…
Robust Kernel-based Distribution Regression
Zhan Yu, Daniel W. C. Ho, Ding-Xuan Zhou
Regularization schemes for regression have been widely studied in learning theory and inverse problems. In this paper, we study distribution regression (DR) which involves two stag…
Mathematical Mechanism on Dynamical System Algorithms of the Ising Model
Bowen Liu, Kaizhi Wang, Dongmei Xiao +1
Various combinatorial optimization NP-hard problems can be reduced to finding the minimizer of an Ising model, which is a discrete mathematical model. It is an intellectual challen…
Estimates on Learning Rates for Multi-Penalty Distribution Regression
Zhan Yu, Daniel W. C. Ho
This paper is concerned with functional learning by utilizing two-stage sampled distribution regression. We study a multi-penalty regularization algorithm for distribution regressi…
Distributed Stochastic Constrained Composite Optimization over Time-Varying Network with a Class of Communication Noise
Zhan Yu, Daniel W. C. Ho, Deming Yuan +1
This paper is concerned with distributed stochastic multi-agent constrained optimization problem over time-varying network with a class of communication noise. This paper considers…
Zeroth-Order Stochastic Block Coordinate Type Methods for Nonconvex Optimization
Zhan Yu, Daniel W. C. Ho
We study (constrained) nonconvex (composite) optimization problems where the decision variables vector can be split into blocks of variables. Random block projection is a popular t…
Distributed Randomized Gradient-Free Mirror Descent Algorithm for Constrained Optimization
Zhan Yu, Daniel W. C. Ho, Deming Yuan
This paper is concerned with multi-agent optimization problem. A distributed randomized gradient-free mirror descent (DRGFMD) method is developed by introducing a randomized gradie…