Anirudh Goyal

Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks

2017 · arXiv (Cornell University)

A major drawback of backpropagation through time (BPTT) is the difficulty of learning long-term dependencies, coming from having to propagate credit information backwards through every single step of the forward computation. This makes BPTT both …

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning

2021 · arXiv (Cornell University)

Inducing causal relationships from observations is a classic problem in machine learning. Most work in causality starts from the premise that the causal variables themselves are observed. However, for AI agents such as robots trying …

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

2016 · PolyPublie (École Polytechnique de Montréal)

We propose zoneout, a novel method for regularizing RNNs. At each timestep, zoneout stochastically forces some hidden units to maintain their previous values. Like dropout, zoneout uses random noise to train a pseudo-ensemble, improving generalization. …

An Actor-Critic Algorithm for Sequence Prediction

2016 · arXiv (Cornell University)

We present an approach to training neural networks to generate sequences using actor-critic methods from reinforcement learning (RL). Current log-likelihood training methods are limited by the discrepancy between their training and testing modes, as models …