Chengqi Zhang

Competitive and Cooperative Heterogeneous Deep Reinforcement Learning

2020

Numerous deep reinforcement learning methods have been proposed, including deterministic, stochastic, and evolutionary-based hybrid methods. However, among these various methodologies, there is no clear winner that consistently outperforms the others in every task in terms …

Multi-graph Multi-label Learning with Dual-granularity Labeling

2021

Graphs are a powerful and versatile data structure that easily captures real life relationship. Multi-graph Multi-label learning (MGML) is a supervised learning task, which aims to learn a Multi-label classifier to label a set of …

DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Recurrent neural nets (RNN) and convolutional neural nets (CNN) are widely used on NLP tasks to capture the long-term and local dependencies, respectively. Attention mechanisms have recently attracted enormous interest due to their highly parallelizable …