Papers
Reversible Recurrent Neural Networks
Matthew MacKay, Paul Vicol, Jimmy Ba et al.
Revisiting $(\epsilon, \gamma, \tau)$-similarity learning for domain adaptation
Sofiane Dhouib, Ievgen Redko
Revisiting Decomposable Submodular Function Minimization with Incidence Relations
Pan Li, Olgica Milenkovic
Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual Detection
Taylor Mordan, Nicolas THOME, Gilles Henaff et al.
Reward learning from human preferences and demonstrations in Atari
Borja Ibarz, Jan Leike, Tobias Pohlen et al.
rho-POMDPs have Lipschitz-Continuous epsilon-Optimal Value Functions
Mathieu Fehr, Olivier Buffet, Vincent Thomas et al.
Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
Abhinav Gupta, Adithyavairavan Murali, Dhiraj Prakashchand Gandhi et al.
Robust Detection of Adversarial Attacks by Modeling the Intrinsic Properties of Deep Neural Networks
Zhihao Zheng, Pengyu Hong
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
RUI GAO, Liyan Xie, Yao Xie et al.
Robust Learning of Fixed-Structure Bayesian Networks
Yu Cheng, Ilias Diakonikolas, Daniel Kane et al.
Robustness of conditional GANs to noisy labels
Kiran K Thekumparampil, Ashish Khetan, Zinan Lin et al.
Robust Subspace Approximation in a Stream
Roie Levin, Anish Prasad Sevekari, David Woodruff
Safe Active Learning for Time-Series Modeling with Gaussian Processes
Christoph Zimmer, Mona Meister, Duy Nguyen-Tuong
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion
Jacob Buckman, Danijar Hafner, George Tucker et al.
Sanity Checks for Saliency Maps
Julius Adebayo, Justin Gilmer, Michael Muelly et al.
Scalable Coordinated Exploration in Concurrent Reinforcement Learning
Maria Dimakopoulou, Ian Osband, Benjamin Van Roy
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation
Matthew O'Kelly, Aman Sinha, Hongseok Namkoong et al.
Scalable Hyperparameter Transfer Learning
Valerio Perrone, Rodolphe Jenatton, Matthias W Seeger et al.
Scalable Laplacian K-modes
Imtiaz Ziko, Eric Granger, Ismail Ben Ayed
Scalable methods for 8-bit training of neural networks
Ron Banner, Itay Hubara, Elad Hoffer et al.
Scalable Robust Matrix Factorization with Nonconvex Loss
Quanming Yao, James Kwok
Scalar Posterior Sampling with Applications
Georgios Theocharous, Zheng Wen, Yasin Abbasi Yadkori et al.
Scaling Gaussian Process Regression with Derivatives
David Eriksson, Kun Dong, Eric Lee et al.