Papers
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.
Rectify Heterogeneous Models with Semantic Mapping
Han-Jia Ye, De-Chuan Zhan, Yuan Jiang 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
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
Zaiyi Chen, Yi Xu, Enhong Chen et al.
Safe Element Screening for Submodular Function Minimization
Weizhong Zhang, Bin Hong, Lin Ma et al.
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
Aaditya Ramdas, Tijana Zrnic, Martin Wainwright et al.
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
Bo Dai, Albert Shaw, Lihong Li et al.
Scalable approximate Bayesian inference for particle tracking data
Ruoxi Sun, Liam Paninski
Scalable Bilinear Pi Learning Using State and Action Features
Yichen Chen, Lihong Li, Mengdi Wang
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints
Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
Trefor Evans, Prasanth Nair
Selecting Representative Examples for Program Synthesis
Yewen Pu, Zachery Miranda, Armando Solar-Lezama et al.