243 citations · 316 across the 8 of their papers we have counts for
8 papers
Fast Matrix Multiplication Without Tears: A Constraint Programming Approach
Arnaud Deza, Chang Liu, Pashootan Vaezipoor +1
It is known that the multiplication of an matrix with an matrix can be performed using fewer multiplications than what the naive approach suggests.…
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 Route via Theory-Guided Residual Network
Chang Liu, Guanjie Zheng, Zhenhui Li
The heavy traffic and related issues have always been concerns for modern cities. With the help of deep learning and reinforcement learning, people have proposed various policies t…
Learning to Simulate on Sparse Trajectory Data
Hua Wei, Chacha Chen, Chang Liu +2
Simulation of the real-world traffic can be used to help validate the transportation policies. A good simulator means the simulated traffic is similar to real-world traffic, which…
Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching
Chang Liu, Zetian Jiang, Runzhong Wang +3
Graph matching (GM) has been a building block in various areas including computer vision and pattern recognition. Despite recent impressive progress, existing deep GM methods often…
GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning
Chang Liu, Huichu Zhang, Weinan Zhang +2
The heavy traffic congestion problem has always been a concern for modern cities. To alleviate traffic congestion, researchers use reinforcement learning (RL) to develop better tra…
ALCNN: Attention-based Model for Fine-grained Demand Inference of Dock-less Shared Bike in New Cities
Chang Liu, Yanan Xu, Yanmin Zhu
In recent years, dock-less shared bikes have been widely spread across many cities in China and facilitate people's lives. However, at the same time, it also raises many problems a…
CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
Huichu Zhang, Siyuan Feng, Chang Liu +7
Traffic signal control is an emerging application scenario for reinforcement learning. Besides being as an important problem that affects people's daily life in commuting, traffic…