Papers
Safe and Nested Subgame Solving for Imperfect-Information Games
Noam Brown, Tuomas Sandholm
Safe Model-based Reinforcement Learning with Stability Guarantees
Felix Berkenkamp, Matteo Turchetta, Angela Schoellig et al.
SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud
Zahra Ghodsi, Tianyu Gu, Siddharth Garg
Saliency-based Sequential Image Attention with Multiset Prediction
Sean Welleck, Jialin Mao, Kyunghyun Cho et al.
Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions
Maria-Florina F Balcan, Hongyang Zhang
Scalable Demand-Aware Recommendation
Jinfeng Yi, Cho-Jui Hsieh, Kush R Varshney et al.
Scalable Generalized Linear Bandits: Online Computation and Hashing
Kwang-Sung Jun, Aniruddha Bhargava, Robert Nowak et al.
Scalable Levy Process Priors for Spectral Kernel Learning
Phillip A Jang, Andrew Loeb, Matthew Davidow et al.
Scalable Log Determinants for Gaussian Process Kernel Learning
Kun Dong, David Eriksson, Hannes Nickisch et al.
Scalable Model Selection for Belief Networks
Zhao Song, Yusuke Muraoka, Ryohei Fujimaki et al.
Scalable Planning with Tensorflow for Hybrid Nonlinear Domains
Ga Wu, Buser Say, Scott Sanner
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
Yuhuai Wu, Elman Mansimov, Roger B Grosse et al.
Scalable Variational Inference for Dynamical Systems
Nico S Gorbach, Stefan Bauer, Joachim M Buhmann
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
Kristof Schütt, Pieter-Jan Kindermans, Huziel Enoc Sauceda Felix et al.
Selective Classification for Deep Neural Networks
Yonatan Geifman, Ran El-Yaniv
Self-Normalizing Neural Networks
Günter Klambauer, Thomas Unterthiner, Andreas Mayr et al.
Self-Supervised Intrinsic Image Decomposition
Michael Janner, Jiajun Wu, Tejas D Kulkarni et al.
Self-supervised Learning of Motion Capture
Hsiao-Yu Tung, Hsiao-Wei Tung, Ersin Yumer et al.
Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding
Arya Mazumdar, Soumyabrata Pal
Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks
Wei-Sheng Lai, Jia-Bin Huang, Ming-Hsuan Yang
Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference
Abhishek Kumar, Prasanna Sattigeri, Tom Fletcher
SGD Learns the Conjugate Kernel Class of the Network
Amit Daniely
Shallow Updates for Deep Reinforcement Learning
Nir Levine, Tom Zahavy, Daniel J Mankowitz et al.
Shape and Material from Sound
Zhoutong Zhang, Qiujia Li, Zhengjia Huang et al.
Sharpness, Restart and Acceleration
Vincent Roulet, Alexandre d'Aspremont