Papers
Robust Attribution Regularization
Jiefeng Chen, Xi Wu, Vaibhav Rastogi et al.
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences
Ehsan Amid, Manfred K. Warmuth, Rohan Anil et al.
Robust exploration in linear quadratic reinforcement learning
Jack Umenberger, Mina Ferizbegovic, Thomas B Schön et al.
Robust Multi-agent Counterfactual Prediction
Alexander Peysakhovich, Christian Kroer, Adam Lerer
Robustness to Adversarial Perturbations in Learning from Incomplete Data
Amir Najafi, Shin-ichi Maeda, Masanori Koyama et al.
Robustness Verification of Tree-based Models
Hongge Chen, Huan Zhang, Si Si et al.
Robust Principal Component Analysis with Adaptive Neighbors
Rui Zhang, Hanghang Tong
Root Mean Square Layer Normalization
Biao Zhang, Rico Sennrich
RSN: Randomized Subspace Newton
Robert Gower, Dmitry Kovalev, Felix Lieder et al.
RUBi: Reducing Unimodal Biases for Visual Question Answering
Remi Cadene, Corentin Dancette, Hedi Ben younes et al.
RUDDER: Return Decomposition for Delayed Rewards
Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich et al.
Saccader: Improving Accuracy of Hard Attention Models for Vision
Gamaleldin Elsayed, Simon Kornblith, Quoc V Le
Safe Exploration for Interactive Machine Learning
Matteo Turchetta, Felix Berkenkamp, Andreas Krause
Same-Cluster Querying for Overlapping Clusters
Wasim Huleihel, Arya Mazumdar, Muriel Medard et al.
Sample Adaptive MCMC
Michael Zhu
Sample Complexity of Learning Mixture of Sparse Linear Regressions
Akshay Krishnamurthy, Arya Mazumdar, Andrew McGregor et al.
Sampled Softmax with Random Fourier Features
Ankit Singh Rawat, Jiecao Chen, Felix Xinnan X Yu et al.
Sample Efficient Active Learning of Causal Trees
Kristjan Greenewald, Dmitriy Katz, Karthikeyan Shanmugam et al.
Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update
Su Young Lee, Choi Sungik, Sae-Young Chung
Sampling Networks and Aggregate Simulation for Online POMDP Planning
Hao(Jackson) Cui, Roni Khardon
Sampling Sketches for Concave Sublinear Functions of Frequencies
Edith Cohen, Ofir Geri
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
Creighton Heaukulani, Mark van der Wilk
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models
Ruoxi Sun, Scott Linderman, Ian Kinsella et al.
Scalable Deep Generative Relational Model with High-Order Node Dependence
Xuhui Fan, Bin Li, Caoyuan Li et al.
Scalable Global Optimization via Local Bayesian Optimization
David Eriksson, Michael Pearce, Jacob Gardner et al.