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Skip to Search Results- 2Representation learning
- 1Augmented Lagrangian optimization
- 1Catastrophic Forgetting
- 1Graph Laplacian
- 1Hyperparameter robustness
- 1Meta-learning
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Fall 2020
Learning online is essential for an agent to perform well in an ever-changing world. An agent has to learn online not only out of necessity --- a non-stationary world might render past learning useless --- but also because continual tracking in a temporally coherent world can result in better...
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Spring 2024
The ability to learn good representations of states is essential for solving large reinforcement learning problems, where exploration, generalization, and transfer are particularly challenging. The Laplacian representation is a promising approach to address these problems by inducing intrinsic...