360 citations · 2.7k across the 150 of their papers we have counts for
5 papers · 1 filter
Policy Gradient Methods for Off-policy Control
Lucas Lehnert, Doina Precup
Off-policy learning refers to the problem of learning the value function of a way of behaving, or policy, while following a different policy. Gradient-based off-policy learning alg…
Conditional Computation in Neural Networks for faster models
Emmanuel Bengio, Pierre-Luc Bacon, Joelle Pineau +1
Deep learning has become the state-of-art tool in many applications, but the evaluation and training of deep models can be time-consuming and computationally expensive. The conditi…
Testing Visual Attention in Dynamic Environments
Philip Bachman, David Krueger, Doina Precup
We investigate attention as the active pursuit of useful information. This contrasts with attention as a mechanism for the attenuation of irrelevant information. We also consider t…
Data Generation as Sequential Decision Making
Philip Bachman, Doina Precup
We connect a broad class of generative models through their shared reliance on sequential decision making. Motivated by this view, we develop extensions to an existing model, and t…
Big Data on the Rise: Testing monotonicity of distributions
Clément L. Canonne
The field of property testing of probability distributions, or distribution testing, aims to provide fast and (most likely) correct answers to questions pertaining to specific aspe…