52 citations · 66 across the 3 of their papers we have counts for
6 papers
A Survey for Solving Mixed Integer Programming via Machine Learning
Jiayi Zhang, Chang Liu, Junchi Yan +3
This paper surveys the trend of leveraging machine learning to solve mixed integer programming (MIP) problems. Theoretically, MIP is an NP-hard problem, and most of the combinatori…
Learning to Select Cuts for Efficient Mixed-Integer Programming
Zeren Huang, Kerong Wang, Furui Liu +6
Cutting plane methods play a significant role in modern solvers for tackling mixed-integer programming (MIP) problems. Proper selection of cuts would remove infeasible solutions in…
Bilevel Learning Model Towards Industrial Scheduling
Longkang Li, Hui-Ling Zhen, Mingxuan Yuan +5
Automatic industrial scheduling, aiming at optimizing the sequence of jobs over limited resources, is widely needed in manufacturing industries. However, existing scheduling system…
Pareto Multi-Task Learning
Xi Lin, Hui-Ling Zhen, Zhenhua Li +2
Multi-task learning is a powerful method for solving multiple correlated tasks simultaneously. However, it is often impossible to find one single solution to optimize all the tasks…
A Batched Scalable Multi-Objective Bayesian Optimization Algorithm
Xi Lin, Hui-Ling Zhen, Zhenhua Li +2
The surrogate-assisted optimization algorithm is a promising approach for solving expensive multi-objective optimization problems. However, most existing surrogate-assisted multi-o…
Nonlinear Collaborative Scheme for Deep Neural Networks
Hui-Ling Zhen, Xi Lin, Alan Z. Tang +3
Conventional research attributes the improvements of generalization ability of deep neural networks either to powerful optimizers or the new network design. Different from them, in…