Papers
Compressing Gradient Optimizers via Count-Sketches
Ryan Spring, Anastasios Kyrillidis, Vijai Mohan et al.
Dual Entangled Polynomial Code: Three-Dimensional Coding for Distributed Matrix Multiplication
Pedro Soto, Jun Li, Xiaodi Fan
MASS: Masked Sequence to Sequence Pre-training for Language Generation
Kaitao Song, Xu Tan, Tao Qin et al.
Revisiting the Softmax Bellman Operator: New Benefits and New Perspective
Zhao Song, Ron Parr, Lawrence Carin
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
Hwanjun Song, Minseok Kim, Jae-Gil Lee
Distribution calibration for regression
Hao Song, Tom Diethe, Meelis Kull et al.
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
Kyunghwan Son, Daewoo Kim, Wan Ju Kang et al.
The Evolved Transformer
David So, Quoc Le, Chen Liang
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
Edward Smith, Scott Fujimoto, Adriana Romero et al.
kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection
Lotfi Slim, Clément Chatelain, Chloe-Agathe Azencott et al.
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation
Sahil Singla, Eric Wallace, Shi Feng et al.
Non-Parametric Priors For Generative Adversarial Networks
Rajhans Singh, Pavan Turaga, Suren Jayasuriya et al.
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
Umut Simsekli, Levent Sagun, Mert Gurbuzbalaban
Refined Complexity of PCA with Outliers
Kirill Simonov, Fedor Fomin, Petr Golovach et al.
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension
Carl-Johann Simon-Gabriel, Yann Ollivier, Leon Bottou et al.
Revisiting precision recall definition for generative modeling
Loic Simon, Ryan Webster, Julien Rabin
Rehashing Kernel Evaluation in High Dimensions
Paris Siminelakis, Kexin Rong, Peter Bailis et al.
Model-Based Active Exploration
Pranav Shyam, Wojciech Jaśkowski, Faustino Gomez
Scalable Training of Inference Networks for Gaussian-Process Models
Jiaxin Shi, Mohammad Emtiyaz Khan, Jun Zhu
Replica Conditional Sequential Monte Carlo
Alex Shestopaloff, Arnaud Doucet
Learning with Bad Training Data via Iterative Trimmed Loss Minimization
Yanyao Shen, Sujay Sanghavi
Hessian Aided Policy Gradient
Zebang Shen, Alejandro Ribeiro, Hamed Hassani et al.
Mixture Models for Diverse Machine Translation: Tricks of the Trade
Tianxiao Shen, Myle Ott, Michael Auli et al.
Learning to Clear the Market
Weiran Shen, Sebastien Lahaie, Renato Paes Leme