Papers
9,944 papers found
Reinforcement Learning in Robust Markov Decision Processes
Shiau Hong Lim, Huan Xu, Shie Mannor
Training and Analysing Deep Recurrent Neural Networks
Michiel Hermans, Benjamin Schrauwen
Learning Multi-level Sparse Representations
Ferran Diego Andilla, Fred A. Hamprecht
An Approximate, Efficient LP Solver for LP Rounding
Srikrishna Sridhar, Stephen Wright, Christopher Re et al.
Regression-tree Tuning in a Streaming Setting
Samory Kpotufe, Francesco Orabona
Dropout Training as Adaptive Regularization
Stefan Wager, Sida Wang, Percy Liang
Prior-free and prior-dependent regret bounds for Thompson Sampling
Sebastien Bubeck, Che-Yu Liu
Efficient Algorithm for Privately Releasing Smooth Queries
Ziteng Wang, Kai Fan, Jiaqi Zhang et al.
Reward Mapping for Transfer in Long-Lived Agents
Xiaoxiao Guo, Satinder Singh, Richard L. Lewis
(More) Efficient Reinforcement Learning via Posterior Sampling
Ian Osband, Daniel Russo, Benjamin Van Roy
Latent Maximum Margin Clustering
Guang-Tong Zhou, Tian Lan, Arash Vahdat et al.
Learning invariant representations and applications to face verification
Qianli Liao, Joel Z. Leibo, Tomaso Poggio
Reasoning With Neural Tensor Networks for Knowledge Base Completion
Richard Socher, Danqi Chen, Christopher D. Manning et al.
Latent Structured Active Learning
Wenjie Luo, Alex Schwing, Raquel Urtasun
Policy Shaping: Integrating Human Feedback with Reinforcement Learning
Shane Griffith, Kaushik Subramanian, Jonathan Scholz et al.
Beyond Disagreement-Based Agnostic Active Learning
Chicheng Zhang, Kamalika Chaudhuri
Near-optimal Reinforcement Learning in Factored MDPs
Ian Osband, Benjamin Van Roy
Difference of Convex Functions Programming for Reinforcement Learning
Bilal Piot, Matthieu Geist, Olivier Pietquin
Deep Learning Face Representation by Joint Identification-Verification
Yi Sun, Yuheng Chen, Xiaogang Wang et al.
Recurrent Models of Visual Attention
Volodymyr Mnih, Nicolas Heess, Alex Graves et al.
The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification
Been Kim, Cynthia Rudin, Julie A Shah
Learning a Concept Hierarchy from Multi-labeled Documents
Viet-An Nguyen, Jordan L Ying, Philip Resnik et al.
Metric Learning for Temporal Sequence Alignment
Damien Garreau, Rémi Lajugie, Sylvain Arlot et al.
Pre-training of Recurrent Neural Networks via Linear Autoencoders
Luca Pasa, Alessandro Sperduti
Algorithm selection by rational metareasoning as a model of human strategy selection
Falk Lieder, Dillon Plunkett, Jessica B Hamrick et al.