7 citations · 11 across the 6 of their papers we have counts for
6 papers
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
Nikhil Vyas, Depen Morwani, Rosie Zhao +3
The success of SGD in deep learning has been ascribed by prior works to the implicit bias induced by finite batch sizes ("SGD noise"). While prior works focused on offline learning…
Policy Gradient Methods in the Presence of Symmetries and State Abstractions
Prakash Panangaden, Sahand Rezaei-Shoshtari, Rosie Zhao +2
Reinforcement learning (RL) on high-dimensional and complex problems relies on abstraction for improved efficiency and generalization. In this paper, we study abstraction in the co…
Loss of Plasticity in Continual Deep Reinforcement Learning
Zaheer Abbas, Rosie Zhao, Joseph Modayil +2
The ability to learn continually is essential in a complex and changing world. In this paper, we characterize the behavior of canonical value-based deep reinforcement learning (RL)…
Continuous MDP Homomorphisms and Homomorphic Policy Gradient
Sahand Rezaei-Shoshtari, Rosie Zhao, Prakash Panangaden +2
Abstraction has been widely studied as a way to improve the efficiency and generalization of reinforcement learning algorithms. In this paper, we study abstraction in the continuou…
Bridging the gap between supervised classification and unsupervised topic modelling for social-media assisted crisis management
Mikael Brunila, Rosie Zhao, Andrei Mircea +2
Social media such as Twitter provide valuable information to crisis managers and affected people during natural disasters. Machine learning can help structure and extract informati…
A Study of Policy Gradient on a Class of Exactly Solvable Models
Gavin McCracken, Colin Daniels, Rosie Zhao +3
Policy gradient methods are extensively used in reinforcement learning as a way to optimize expected return. In this paper, we explore the evolution of the policy parameters, for a…