Papers
Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope
Eric Wong, Zico Kolter
Provable Variable Selection for Streaming Features
Jing Wang, Jie Shen, Ping Li
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing—and Back
Elliot Meyerson, Risto Miikkulainen
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder et al.
QuantTree: Histograms for Change Detection in Multivariate Data Streams
Giacomo Boracchi, Diego Carrera, Cristiano Cervellera et al.
Quasi-Monte Carlo Variational Inference
Alexander Buchholz, Florian Wenzel, Stephan Mandt
Quickshift++: Provably Good Initializations for Sample-Based Mean Shift
Heinrich Jiang, Jennifer Jang, Samory Kpotufe
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
Yichi Zhou, Jun Zhu, Jingwei Zhuo
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks
Jinsung Yoon, James Jordon, Mihaela Schaar
Randomized Block Cubic Newton Method
Nikita Doikov, Peter Richtarik, University Edinburgh
Ranking Distributions based on Noisy Sorting
Adil El Mesaoudi-Paul, Eyke Hüllermeier, Robert Busa-Fekete
Rapid Adaptation with Conditionally Shifted Neurons
Tsendsuren Munkhdalai, Xingdi Yuan, Soroush Mehri et al.
Recurrent Predictive State Policy Networks
Ahmed Hefny, Zita Marinho, Wen Sun et al.
Regret Minimization for Partially Observable Deep Reinforcement Learning
Peter Jin, Kurt Keutzer, Sergey Levine
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
Yangchen Pan, Amir-massoud Farahmand, Martha White et al.
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
Xi Wu, Uyeong Jang, Jiefeng Chen et al.
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu, Chengtao Li, Yonglong Tian et al.
Representation Tradeoffs for Hyperbolic Embeddings
Frederic Sala, Chris De Sa, Albert Gu et al.
Residual Unfairness in Fair Machine Learning from Prejudiced Data
Nathan Kallus, Angela Zhou
Revealing Common Statistical Behaviors in Heterogeneous Populations
Andrey Zhitnikov, Rotem Mulayoff, Tomer Michaeli
Reviving and Improving Recurrent Back-Propagation
Renjie Liao, Yuwen Xiong, Ethan Fetaya et al.
Riemannian Stochastic Recursive Gradient Algorithm
Hiroyuki Kasai, Hiroyuki Sato, Bamdev Mishra
RLlib: Abstractions for Distributed Reinforcement Learning
Eric Liang, Richard Liaw, Robert Nishihara et al.
Robust and Scalable Models of Microbiome Dynamics
Travis Gibson, Georg Gerber