Papers
SGD without Replacement: Sharper Rates for General Smooth Convex Functions
Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli
Shallow-Deep Networks: Understanding and Mitigating Network Overthinking
Yigitcan Kaya, Sanghyun Hong, Tudor Dumitras
Shape Constraints for Set Functions
Andrew Cotter, Maya Gupta, Heinrich Jiang et al.
Similarity of Neural Network Representations Revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee et al.
Simple Black-box Adversarial Attacks
Chuan Guo, Jacob Gardner, Yurong You et al.
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization
Michael Metel, Akiko Takeda
Simplifying Graph Convolutional Networks
Felix Wu, Amauri Souza, Tianyi Zhang et al.
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
Antoine Liutkus, Umut Simsekli, Szymon Majewski et al.
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
Natasha Jaques, Angeliki Lazaridou, Edward Hughes et al.
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning
Marvin Zhang, Sharad Vikram, Laura Smith et al.
Sorting Out Lipschitz Function Approximation
Cem Anil, James Lucas, Roger Grosse
Sparse Extreme Multi-label Learning with Oracle Property
Weiwei Liu, Xiaobo Shen
Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data
Luigi Antelmi, Nicholas Ayache, Philippe Robert et al.
Spectral Approximate Inference
Sejun Park, Eunho Yang, Se-Young Yun et al.
Spectral Clustering of Signed Graphs via Matrix Power Means
Pedro Mercado, Francesco Tudisco, Matthias Hein
Stable and Fair Classification
Lingxiao Huang, Nisheeth Vishnoi
Stable-Predictive Optimistic Counterfactual Regret Minimization
Gabriele Farina, Christian Kroer, Noam Brown et al.
State-Regularized Recurrent Neural Networks
Cheng Wang, Mathias Niepert
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
Alex Lamb, Jonathan Binas, Anirudh Goyal et al.
Static Automatic Batching In TensorFlow
Ashish Agarwal
Statistical Foundations of Virtual Democracy
Anson Kahng, Min Kyung Lee, Ritesh Noothigattu et al.
Statistics and Samples in Distributional Reinforcement Learning
Mark Rowland, Robert Dadashi, Saurabh Kumar et al.
Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging
Ping-Chun Hsieh, Xi Liu, Anirban Bhattacharya et al.
Stein Point Markov Chain Monte Carlo
Wilson Ye Chen, Alessandro Barp, Francois-Xavier Briol et al.
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Wouter Kool, Herke Van Hoof, Max Welling