91 citations · 204 across the 5 of their papers we have counts for
5 papers
Ethical and social risks of harm from Language Models
Laura Weidinger, John Mellor, Maribeth Rauh +20
This paper aims to help structure the risk landscape associated with large-scale Language Models (LMs). In order to foster advances in responsible innovation, an in-depth understan…
Wasserstein Fair Classification
Ray Jiang, Aldo Pacchiano, Tom Stepleton +2
We propose an approach to fair classification that enforces independence between the classifier outputs and sensitive information by minimizing Wasserstein-1 distances. The approac…
Low-pass Recurrent Neural Networks - A memory architecture for longer-term correlation discovery
Thomas Stepleton, Razvan Pascanu, Will Dabney +3
Reinforcement learning (RL) agents performing complex tasks must be able to remember observations and actions across sizable time intervals. This is especially true during the init…
Safe and Efficient Off-Policy Reinforcement Learning
Rémi Munos, Tom Stepleton, Anna Harutyunyan +1
In this work, we take a fresh look at some old and new algorithms for off-policy, return-based reinforcement learning. Expressing these in a common form, we derive a novel algorith…
Q() with Off-Policy Corrections
Anna Harutyunyan, Marc G. Bellemare, Tom Stepleton +1
We propose and analyze an alternate approach to off-policy multi-step temporal difference learning, in which off-policy returns are corrected with the current Q-function in terms o…