Gradient descent-trained neural networks operate effectively even in overparameterized settings with random weight initialization, often finding global optimum solutions despite the non-convex nature ...

Abstract: Learning a policy with great generalization to unseen environments remains challenging but critical in visual reinforcement learning. Despite the success of augmentation combination in the ...

SGD methods try to minimize the error on observed examples by adjusting the weight vector after each example by a small amount in the direction that would most reduce ...

Conceptual overview of this work. (A) Animals have goals, which they must learn to achieve. In this case, consider revising a paper. (B) Some feedback signals (e.g., from reviewers or co-authors) will ...

Class Summary & Notes from OMS CS7642 - Reinforcement Learning - CS7642-Reinforcement-Learning/Module 8 Generalization/Week 8 Generalization/Policy Gradient Methods.md at main · ...