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A Definition of Continual Reinforcement Learning
In a standard view of the reinforcement learning problem, an agent's goal is to efficiently identify a policy that maximizes long-term reward.
Generalized Weighted Path Consistency for Mastering Atari Games
Reinforcement learning with the help of neural-guided search consumes huge computational resources to achieve remarkable performance.
Provable Training for Graph Contrastive Learning Yue Y u
Considering the complex graph structure, are some nodes consistently well-trained and following this principle even with different graph augmentations?
United We Stand, Divided We Fall: Fingerprinting Deep Neural Networks via Adversarial Trajectories
In recent years, deep neural networks (DNNs) have witnessed extensive applications, and protecting their intellectual property (IP) is thus crucial. As a noninvasive way for model IP protection, model fingerprinting has become popular.