activity
20192021
most citedEnumerating Chemical Graphs with Two Disjoint Cycles Satisfying Given Path Frequency Specifications

3 citations · 4 across the 3 of their papers we have counts for

collaborators

8 papers

math.OC2021

Value-Gradient based Formulation of Optimal Control Problem and Machine Learning Algorithm

Alain Bensoussan, Jiayue Han, Sheung Chi Phillip Yam +1

Optimal control problem is typically solved by first finding the value function through Hamilton-Jacobi equation (HJE) and then taking the minimizer of the Hamiltonian to obtain th…

math.NA2020

Projection Method for Saddle Points of Energy Functional in Metric

Shuting Gu, Ling Lin, Xiang Zhou

Saddle points play important roles as the transition states of activated process in gradient system driven by energy functional. However, for the same energy functional, the saddle…

cs.LG20201 cited

Machine Learning and Control Theory

Alain Bensoussan, Yiqun Li, Dinh Phan Cao Nguyen +3

We survey in this article the connections between Machine Learning and Control Theory. Control Theory provide useful concepts and tools for Machine Learning. Conversely Machine Lea…

cs.DS20203 cited

Enumerating Chemical Graphs with Two Disjoint Cycles Satisfying Given Path Frequency Specifications

Kyousuke Yamashita, Ryuji Masui, Xiang Zhou +4

Enumerating chemical graphs satisfying given constraints is a fundamental problem in mathematical and computational chemistry, and plays an essential part in a recently proposed fr…

stat.CO2020

Explicit Estimation of Derivatives from Data and Differential Equations by Gaussian Process Regression

Hongqiao Wang, Xiang Zhou

In this work, we employ the Bayesian inference framework to solve the problem of estimating the solution and particularly, its derivatives, which satisfy a known differential equat…

math.OC2020

Stochastic Modified Equations for Continuous Limit of Stochastic ADMM

Xiang Zhou, Huizhuo Yuan, Chris Junchi Li +1

Stochastic version of alternating direction method of multiplier (ADMM) and its variants (linearized ADMM, gradient-based ADMM) plays a key role for modern large scale machine lear…