In recent years, the optimization and computational intelligence methods have achieved remarkable results in domains including robotics, games, circuit design, and large-scale scheduling engine. This workshop will bring together researchers working at the field of optimization, reinforcement learning, and evolutionary computation, and it will also cover the cutting-edge research both in academic and industrial communities. It aims to help interested researchers both inside and outside of the field gain a high-level view about the current state-of-the-art works and potential directions and applications for future.

Attending the Workshop

The workshop will be hosted at Tactic C, Aloft Shanghai Zhangjiang Haike (上海张江海科雅乐轩酒店).

Please attend the workshop by following the streaming link: http://live.bilibili.com/6438583

Invited Speakers




The workshop schedule is aligned with 9 AM to 6 PM UTC+8.

UTC+8 Talker Title Affiliation
09:00-09:40 Defeng Sun Some Numerical Experiments in Solving Linear Programming Approximately using sGS-ADMM and Its Acceleration The Hong Kong Polytechnic University
09:40-10:05 Amin Banitalebi ML4CO: Is GCNN All You Need? Graph Convolutional Neural Networks Produce Strong Baselines For Combinatorial Optimization Problems, If Tuned and Trained Properly Huawei
10:05-10:15 Coffee Break    
10:15-10:55 Qingfu Zhang Multiobjective Optimization Evolutionary Algorithm based Decomposition City University of Hong Kong
10:55-11:20 Zhendong Lei The Problem of Maximum Satisfiability and Its Extension Huawei
11:20-11:45 Chao Qian Subset Selection by Pareto Optimization: Theories and Practical Algorithms Nanjing University
11:45-14:00 Lunch    
14:00-14:40 Aimin Zhou Expensive Multiobjective Optimization by Relation Learning and Prediction East China Normal University
14:40-15:05 Hang Su The Black-box Optimization on Adversarial Learning Tsinghua University
15:05-15:15 Coffee Break    
15:15-15:55 Xin Xu Reinforcement Learning Methods for Multi-robot Collaborative Decision-Making and Optimal Control National University of Defense Technology
15:55-16:20 Yan Zheng HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation Tianjin University
16:20-17:40 Huiling Zhen, Meng Lu, Xihan Li, Zeren Huang Machine Learning for Solver Optimization Huawei, Shanghai Jiao Tong University, University College London