3 citations · 4 across the 3 of their papers we have counts for
4 papers
Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
Runyu Lu, Peng Zhang, Ruochuan Shi +5
Equilibrium learning in adversarial games is an important topic widely examined in the fields of game theory and reinforcement learning (RL). Pursuit-evasion game (PEG), as an impo…
CL4KGE: A Curriculum Learning Method for Knowledge Graph Embedding
Yang Liu, Chuan Zhou, Peng Zhang +4
Knowledge graph embedding (KGE) constitutes a foundational task, directed towards learning representations for entities and relations within knowledge graphs (KGs), with the object…
Decision-focused Graph Neural Networks for Combinatorial Optimization
Yang Liu, Chuan Zhou, Peng Zhang +3
In recent years, there has been notable interest in investigating combinatorial optimization (CO) problems by neural-based framework. An emerging strategy to tackle these challengi…
Combinatorial Optimization with Automated Graph Neural Networks
Yang Liu, Peng Zhang, Yang Gao +3
In recent years, graph neural networks (GNNs) have become increasingly popular for solving NP-hard combinatorial optimization (CO) problems, such as maximum cut and maximum indepen…