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Found 2 papers, 1 papers with code
Continual Learning on Noisy Data Streams via Self-Purified Replay
Continually learning in the real world must overcome many challenges, among which noisy labels are a common and inevitable issue.
Learning to Schedule Communication in Multi-agent Reinforcement Learning
Many real-world reinforcement learning tasks require multiple agents to make sequential decisions under the agents' interaction, where well-coordinated actions among the agents are crucial to achieve the target goal better at these tasks.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
