8 papers
Explicit Credit Assignment through Local Rewards and Dependence Graphs in Multi-Agent Reinforcement Learning
Bang Giang Le, Viet Cuong Ta
To promote cooperation in Multi-Agent Reinforcement Learning, the reward signals of all agents can be aggregated together, forming global rewards that are commonly known as the ful…
Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning
Bang Giang Le, Viet Cuong Ta
Cooperative multi-agent reinforcement learning assumes each agent shares the same reward function and can be trained effectively using the Trust Region framework of single-agent. I…
Balancing Knowledge Distillation for Imbalance Learning with Bilevel Optimization
Anh B. H. Nguyen, Ba Tho Phan, Viet Cuong Ta
Knowledge distillation transfers knowledge from a high capacity teacher to a compact student using a mixture of hard and soft losses. On imbalanced data, a fixed weighting between…
Efficient Bilevel Optimization for Meta Label Correction in Noisy Label Learning
Ba Hoang Anh Nguyen, Viet Cuong Ta
Training a deep neural network with noisy labels could reduce data annotation cost but may introduce noise into the learned model. In meta label correction approaches, an additiona…
Sequence Diffusion Model for Temporal Link Prediction in Continuous-Time Dynamic Graph
Nguyen Minh Duc, Viet Cuong Ta
Temporal link prediction in dynamic graphs is a fundamental problem in many real-world systems. Existing temporal graph neural networks mainly focus on learning representations of…
Resolve Highway Conflict in Multi-Autonomous Vehicle Controls with Local State Attention
Xuan Duy Ta, Bang Giang Le, Thanh Ha Le +1
In mixed-traffic environments, autonomous vehicles must adapt to human-controlled vehicles and other unusual driving situations. This setting can be framed as a multi-agent reinfor…