Papers
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan, Alexander Pritzel, Charles Blundell
Imagination-Augmented Agents for Deep Reinforcement Learning
Sébastien Racanière, Theophane Weber, David Reichert et al.
Towards Generalization and Simplicity in Continuous Control
Aravind Rajeswaran, Kendall Lowrey, Emanuel V. Todorov et al.
Certified Defenses for Data Poisoning Attacks
Jacob Steinhardt, Pang Wei W Koh, Percy Liang
GP CaKe: Effective brain connectivity with causal kernels
Luca Ambrogioni, Max Hinne, Marcel Van Gerven et al.
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
Siddharth N, Brooks Paige, Jan-Willem van de Meent et al.
On Blackbox Backpropagation and Jacobian Sensing
Krzysztof M Choromanski, Vikas Sindhwani
Learning a Multi-View Stereo Machine
Abhishek Kar, Christian Häne, Jitendra Malik
Scalable Demand-Aware Recommendation
Jinfeng Yi, Cho-Jui Hsieh, Kush R Varshney et al.
Optimized Pre-Processing for Discrimination Prevention
Flavio Calmon, Dennis Wei, Bhanukiran Vinzamuri et al.
Fast Black-box Variational Inference through Stochastic Trust-Region Optimization
Jeffrey Regier, Michael I Jordan, Jon McAuliffe
Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces
Daniel Milstein, Jason Pacheco, Leigh Hochberg et al.
Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search
Mohammad Ali Bashiri, Xinhua Zhang
Bandits Dueling on Partially Ordered Sets
Julien Audiffren, Liva Ralaivola
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models
Chris Oates, Steven Niederer, Angela Lee et al.
Scalable Planning with Tensorflow for Hybrid Nonlinear Domains
Ga Wu, Buser Say, Scott Sanner
Rotting Bandits
Nir Levine, Koby Crammer, Shie Mannor
A Linear-Time Kernel Goodness-of-Fit Test
Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo et al.
Fair Clustering Through Fairlets
Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi et al.
Scalable Log Determinants for Gaussian Process Kernel Learning
Kun Dong, David Eriksson, Hannes Nickisch et al.
Ranking Data with Continuous Labels through Oriented Recursive Partitions
Stéphan Clémençon, Mastane Achab
A Decomposition of Forecast Error in Prediction Markets
Miro Dudik, Sebastien Lahaie, Ryan M Rogers et al.
Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach
Emmanouil Platanios, Hoifung Poon, Tom M. Mitchell et al.
Causal Effect Inference with Deep Latent-Variable Models
Christos Louizos, Uri Shalit, Joris M. Mooij et al.