
Neural Production Systems
Visual environments are structured, consisting of distinct objects or en...
read it

Coordination Among Neural Modules Through a Shared Global Workspace
Deep learning has seen a movement away from representing examples with a...
read it

Towards Causal Representation Learning
The two fields of machine learning and graphical causality arose and dev...
read it

On the Convergence of Continuous Constrained Optimization for Structure Learning
Structure learning of directed acyclic graphs (DAGs) is a fundamental pr...
read it

Amortized learning of neural causal representations
Causal models can compactly and efficiently encode the datagenerating p...
read it

Causally Correct Partial Models for Reinforcement Learning
In reinforcement learning, we can learn a model of future observations a...
read it

Learning Neural Causal Models from Unknown Interventions
Metalearning over a set of distributions can be interpreted as learning...
read it

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
In modelbased reinforcement learning, the agent interleaves between mod...
read it

hdetach: Modifying the LSTM Gradient Towards Better Optimization
Recurrent neural networks are known for their notorious exploding and va...
read it

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding
Learning longterm dependencies in extended temporal sequences requires ...
read it

Focused Hierarchical RNNs for Conditional Sequence Processing
Recurrent Neural Networks (RNNs) with attention mechanisms have obtained...
read it

A Deep Reinforcement Learning Chatbot (Short Version)
We present MILABOT: a deep reinforcement learning chatbot developed by t...
read it

Ethical Challenges in DataDriven Dialogue Systems
The use of dialogue systems as a medium for humanmachine interaction is...
read it

ZForcing: Training Stochastic Recurrent Networks
Many efforts have been devoted to training generative latent variable mo...
read it

ACtuAL: ActorCritic Under Adversarial Learning
Generative Adversarial Networks (GANs) are a powerful framework for deep...
read it

Sparse Attentive Backtracking: LongRange Credit Assignment in Recurrent Networks
A major drawback of backpropagation through time (BPTT) is the difficult...
read it

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net
We propose a novel method to directly learn a stochastic transition oper...
read it

A Deep Reinforcement Learning Chatbot
We present MILABOT: a deep reinforcement learning chatbot developed by t...
read it

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations
We propose zoneout, a novel method for regularizing RNNs. At each timest...
read it

Cascading Bandits for LargeScale Recommendation Problems
Most recommender systems recommend a list of items. The user examines th...
read it

Transferring Knowledge from a RNN to a DNN
Deep Neural Network (DNN) acoustic models have yielded many stateofthe...
read it
Nan Rosemary Ke
is this you? claim profile
PHD Student at MILA, Montreal institute of Learning Algorithms