no code implementations • 13 Nov 2023 • Depen Morwani, Benjamin L. Edelman, Costin-Andrei Oncescu, Rosie Zhao, Sham Kakade
Understanding the internal representations learned by neural networks is a cornerstone challenge in the science of machine learning.
no code implementations • 14 Jun 2023 • Nikhil Vyas, Depen Morwani, Rosie Zhao, Gal Kaplun, Sham Kakade, Boaz Barak
The success of SGD in deep learning has been ascribed by prior works to the implicit bias induced by high learning rate or small batch size ("SGD noise").
2 code implementations • 9 May 2023 • Prakash Panangaden, Sahand Rezaei-Shoshtari, Rosie Zhao, David Meger, Doina Precup
Our policy gradient results allow for leveraging approximate symmetries of the environment for policy optimization.
no code implementations • 13 Mar 2023 • Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White, Marlos C. Machado
The ability to learn continually is essential in a complex and changing world.
1 code implementation • 15 Sep 2022 • Sahand Rezaei-Shoshtari, Rosie Zhao, Prakash Panangaden, David Meger, Doina Precup
Abstraction has been widely studied as a way to improve the efficiency and generalization of reinforcement learning algorithms.
no code implementations • EACL (AdaptNLP) 2021 • Mikael Brunila, Rosie Zhao, Andrei Mircea, Sam Lumley, Renee Sieber
Social media such as Twitter provide valuable information to crisis managers and affected people during natural disasters.
no code implementations • 3 Nov 2020 • Gavin McCracken, Colin Daniels, Rosie Zhao, Anna Brandenberger, Prakash Panangaden, Doina Precup
Policy gradient methods are extensively used in reinforcement learning as a way to optimize expected return.