1 citations · 6 across the 25 of their papers we have counts for
7 papers · 1 filter
Diversifying Message Aggregation in Multi-Agent Communication via Normalized Tensor Nuclear Norm Regularization
Yuanzhao Zhai, Kele Xu, Bo Ding +3
Aggregating messages is a key component for the communication of multi-agent reinforcement learning (Comm-MARL). Recently, it has witnessed the prevalence of graph attention networ…
Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning
Zijian Gao, Kele Xu, Yuanzhao Zhai +4
Under sparse extrinsic reward settings, reinforcement learning has remained challenging, despite surging interests in this field. Previous attempts suggest that intrinsic reward ca…
Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration
Zijian Gao, YiYing Li, Kele Xu +5
The sparsity of extrinsic rewards poses a serious challenge for reinforcement learning (RL). Currently, many efforts have been made on curiosity which can provide a representative…
Trusted Multi-Scale Classification Framework for Whole Slide Image
Ming Feng, Kele Xu, Nanhui Wu +4
Despite remarkable efforts been made, the classification of gigapixels whole-slide image (WSI) is severely restrained from either the constrained computing resources for the whole…
Nuclear Norm Maximization Based Curiosity-Driven Learning
Chao Chen, Zijian Gao, Kele Xu +5
To handle the sparsity of the extrinsic rewards in reinforcement learning, researchers have proposed intrinsic reward which enables the agent to learn the skills that might come in…
Unsupervised Voice-Face Representation Learning by Cross-Modal Prototype Contrast
Boqing Zhu, Kele Xu, Changjian Wang +4
We present an approach to learn voice-face representations from the talking face videos, without any identity labels. Previous works employ cross-modal instance discrimination task…
Multi-task Pre-training Language Model for Semantic Network Completion
Da Li, Sen Yang, Kele Xu +3
Semantic networks, such as the knowledge graph, can represent the knowledge leveraging the graph structure. Although the knowledge graph shows promising values in natural language…