200 citations · 636 across the 27 of their papers we have counts for
5 papers · 1 filter
Adversarial Gain
Peter Henderson, Koustuv Sinha, Rosemary Nan Ke +1
Adversarial examples can be defined as inputs to a model which induce a mistake - where the model output is different than that of an oracle, perhaps in surprising or malicious way…
h-detach: Modifying the LSTM Gradient Towards Better Optimization
Devansh Arpit, Bhargav Kanuparthi, Giancarlo Kerg +3
Recurrent neural networks are known for their notorious exploding and vanishing gradient problem (EVGP). This problem becomes more evident in tasks where the information needed to…
Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk +4
Learning long-term dependencies in extended temporal sequences requires credit assignment to events far back in the past. The most common method for training recurrent neural netwo…
Focused Hierarchical RNNs for Conditional Sequence Processing
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni +6
Recurrent Neural Networks (RNNs) with attention mechanisms have obtained state-of-the-art results for many sequence processing tasks. Most of these models use a simple form of enco…
A Deep Reinforcement Learning Chatbot (Short Version)
Iulian V. Serban, Chinnadhurai Sankar, Mathieu Germain +15
We present MILABOT: a deep reinforcement learning chatbot developed by the Montreal Institute for Learning Algorithms (MILA) for the Amazon Alexa Prize competition. MILABOT is capa…