Co-occurring keywords · papers mentioning both
Papers
Strategic Tasks for Explainable Reinforcement Learning
AAAI 2019
Streamlined Dense Video Captioning
CVPR 2019
StrokeNet: A Neural Painting Environment
ICLR 2019
Structure Learning for Safe Policy Improvement
IJCAI 2019
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
NeurIPS 2019
Summary Level Training of Sentence Rewriting for Abstractive Summarization
EMNLP 2019
Surveys without Questions: A Reinforcement Learning Approach
AAAI 2019
Switch-Based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning
AAAI 2019
Task Agnostic Meta-Learning for Few-Shot Learning
CVPR 2019
Teaching Robots to Interact with Humans in a Smart Environment
IJCAI 2019
The Expected-Length Model of Options
IJCAI 2019
The Laplacian in RL: Learning Representations with Efficient Approximations
ICLR 2019
The Natural Language of Actions
ICML 2019
Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning
AISTATS 2019
The Termination Critic
AISTATS 2019
The Utility of Sparse Representations for Control in Reinforcement Learning
AAAI 2019
TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning
ICML 2019
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
ICML 2019
Towards Comprehensive Description Generation from Factual Attribute-value Tables
ACL 2019
Towards Governing Agent’s Efficacy: Action-Conditional $β$-VAE for Deep Transparent Reinforcement Learning
ACML 2019
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents
NeurIPS 2019
Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling
NeurIPS 2019
Towards Sequence-to-Sequence Reinforcement Learning for Constraint Solving with Constraint-Based Local Search
AAAI 2019
Trainable Undersampling for Class-Imbalance Learning
AAAI 2019
Transfer in Deep Reinforcement Learning Using Knowledge Graphs
EMNLP 2019