18 citations · 50 across the 7 of their papers we have counts for
7 papers
Unsupervised Learning for Solving the Travelling Salesman Problem
Yimeng Min, Yiwei Bai, Carla P. Gomes
We propose UTSP, an unsupervised learning (UL) framework for solving the Travelling Salesman Problem (TSP). We train a Graph Neural Network (GNN) using a surrogate loss. The GNN ou…
Automating Crystal-Structure Phase Mapping: Combining Deep Learning with Constraint Reasoning
Di Chen, Yiwei Bai, Sebastian Ament +7
Crystal-structure phase mapping is a core, long-standing challenge in materials science that requires identifying crystal structures, or mixtures thereof, in synthesized materials.…
Fairness of Exposure in Stochastic Bandits
Lequn Wang, Yiwei Bai, Wen Sun +1
Contextual bandit algorithms have become widely used for recommendation in online systems (e.g. marketplaces, music streaming, news), where they now wield substantial influence on…
Zero Training Overhead Portfolios for Learning to Solve Combinatorial Problems
Yiwei Bai, Wenting Zhao, Carla P. Gomes
There has been an increasing interest in harnessing deep learning to tackle combinatorial optimization (CO) problems in recent years. Typical CO deep learning approaches leverage t…
Deep Reasoning Networks: Thinking Fast and Slow
Di Chen, Yiwei Bai, Wenting Zhao +3
We introduce Deep Reasoning Networks (DRNets), an end-to-end framework that combines deep learning with reasoning for solving complex tasks, typically in an unsupervised or weakly-…
Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Network
Johan Bjorck, Yiwei Bai, Xiaojian Wu +3
Cascades represent rapid changes in networks. A cascading phenomenon of ecological and economic impact is the spread of invasive species in geographic landscapes. The most promisin…
A Study of AI Population Dynamics with Million-agent Reinforcement Learning
Yaodong Yang, Lantao Yu, Yiwei Bai +4
We conduct an empirical study on discovering the ordered collective dynamics obtained by a population of intelligence agents, driven by million-agent reinforcement learning. Our in…