4 papers
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking
Eric Crawford, Joelle Pineau
The ability to detect and track objects in the visual world is a crucial skill for any intelligent agent, as it is a necessary precursor to any object-level reasoning process. More…
Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning
Srinivas Venkattaramanujam, Eric Crawford, Thang Doan +1
Goal-conditioned policies are used in order to break down complex reinforcement learning (RL) problems by using subgoals, which can be defined either in state space or in a latent…
Sequential Coordination of Deep Models for Learning Visual Arithmetic
Eric Crawford, Guillaume Rabusseau, Joelle Pineau
Achieving machine intelligence requires a smooth integration of perception and reasoning, yet models developed to date tend to specialize in one or the other; sophisticated manipul…
BanditSum: Extractive Summarization as a Contextual Bandit
Yue Dong, Yikang Shen, Eric Crawford +2
In this work, we propose a novel method for training neural networks to perform single-document extractive summarization without heuristically-generated extractive labels. We call…