Papers
Consistent On-Line Off-Policy Evaluation
Assaf Hallak, Shie Mannor
Constrained Policy Optimization
Joshua Achiam, David Held, Aviv Tamar et al.
Contextual Decision Processes with low Bellman rank are PAC-Learnable
Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal et al.
Continual Learning Through Synaptic Intelligence
Friedemann Zenke, Ben Poole, Surya Ganguli
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization
Qunwei Li, Yi Zhou, Yingbin Liang et al.
Convexified Convolutional Neural Networks
Yuchen Zhang, Percy Liang, Martin J. Wainwright
Convex Phase Retrieval without Lifting via PhaseMax
Tom Goldstein, Christoph Studer
“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions
Yair Carmon, John C. Duchi, Oliver Hinder et al.
Convolutional Sequence to Sequence Learning
Jonas Gehring, Michael Auli, David Grangier et al.
Coordinated Multi-Agent Imitation Learning
Hoang M. Le, Yisong Yue, Peter Carr et al.
Coresets for Vector Summarization with Applications to Network Graphs
Dan Feldman, Sedat Ozer, Daniela Rus
Cost-Optimal Learning of Causal Graphs
Murat Kocaoglu, Alex Dimakis, Sriram Vishwanath
Count-Based Exploration with Neural Density Models
Georg Ostrovski, Marc G. Bellemare, Aäron Oord et al.
Counterfactual Data-Fusion for Online Reinforcement Learners
Andrew Forney, Judea Pearl, Elias Bareinboim
Coupling Distributed and Symbolic Execution for Natural Language Queries
Lili Mou, Zhengdong Lu, Hang Li et al.
Curiosity-driven Exploration by Self-supervised Prediction
Deepak Pathak, Pulkit Agrawal, Alexei A. Efros et al.
Dance Dance Convolution
Chris Donahue, Zachary C. Lipton, Julian McAuley
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
Irina Higgins, Arka Pal, Andrei Rusu et al.
Data-Efficient Policy Evaluation Through Behavior Policy Search
Josiah P. Hanna, Philip S. Thomas, Peter Stone et al.
Deciding How to Decide: Dynamic Routing in Artificial Neural Networks
Mason McGill, Pietro Perona
Decoupled Neural Interfaces using Synthetic Gradients
Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero et al.
DeepBach: a Steerable Model for Bach Chorales Generation
Gaëtan Hadjeres, François Pachet, Frank Nielsen
Deep Bayesian Active Learning with Image Data
Yarin Gal, Riashat Islam, Zoubin Ghahramani
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Shayegan Omidshafiei, Jason Pazis, Christopher Amato et al.
Deep Generative Models for Relational Data with Side Information
Changwei Hu, Piyush Rai, Lawrence Carin