Nan Rosemary Ke

According to our database1, Nan Rosemary Ke authored at least 32 papers between 2011 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2019
Learning Neural Causal Models from Unknown Interventions.
CoRR, 2019

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future.
CoRR, 2019

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms.
CoRR, 2019

Modeling the Long Term Future in Model-Based Reinforcement Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

h-detach: Modifying the LSTM Gradient Towards Better Optimization.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Adversarial Gain.
CoRR, 2018

h-detach: Modifying the LSTM Gradient Towards Better Optimization.
CoRR, 2018

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding.
CoRR, 2018

Focused Hierarchical RNNs for Conditional Sequence Processing.
CoRR, 2018

A Deep Reinforcement Learning Chatbot (Short Version).
CoRR, 2018

Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Focused Hierarchical RNNs for Conditional Sequence Processing.
Proceedings of the 35th International Conference on Machine Learning, 2018

Twin Networks: Matching the Future for Sequence Generation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Ethical Challenges in Data-Driven Dialogue Systems.
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

2017
Ethical Challenges in Data-Driven Dialogue Systems.
CoRR, 2017

Z-Forcing: Training Stochastic Recurrent Networks.
CoRR, 2017

ACtuAL: Actor-Critic Under Adversarial Learning.
CoRR, 2017

Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks.
CoRR, 2017

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net.
CoRR, 2017

A Deep Reinforcement Learning Chatbot.
CoRR, 2017

Twin Networks: Using the Future as a Regularizer.
CoRR, 2017

Z-Forcing: Training Stochastic Recurrent Networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Cascading Bandits for Large-Scale Recommendation Problems.
CoRR, 2016

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.
CoRR, 2016

Cascading Bandits for Large-Scale Recommendation Problems.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

2015
Transferring Knowledge from a RNN to a DNN.
CoRR, 2015

Task Loss Estimation for Sequence Prediction.
CoRR, 2015

Transferring knowledge from a RNN to a DNN.
Proceedings of the INTERSPEECH 2015, 2015

2012
Markerless Visual Control of a Quad-Rotor Micro Aerial Vehicle by Means of On-Board Stereo Processing.
Proceedings of the Autonomous Mobile Systems 2012, 2012

2011
Descriptional Complexity of Determinization and Complementation for Finite Automata.
Proceedings of the Seventeenth Computing: The Australasian Theory Symposium, 2011


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