Papers
Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training
Xuxi Chen, Wuyang Chen, Tianlong Chen et al.
Self-supervised Label Augmentation via Input Transformations
Hankook Lee, Sung Ju Hwang, Jinwoo Shin
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Sen Na, Yuwei Luo, Zhuoran Yang et al.
Semismooth Newton Algorithm for Efficient Projections onto $\ell_1, ∞$-norm Ball
Dejun Chu, Changshui Zhang, Shiliang Sun et al.
Semi-Supervised Learning with Normalizing Flows
Pavel Izmailov, Polina Kirichenko, Marc Finzi et al.
Semi-Supervised StyleGAN for Disentanglement Learning
Weili Nie, Tero Karras, Animesh Garg et al.
Sequence Generation with Mixed Representations
Lijun Wu, Shufang Xie, Yingce Xia et al.
Sequential Cooperative Bayesian Inference
Junqi Wang, Pei Wang, Patrick Shafto
Sequential Transfer in Reinforcement Learning with a Generative Model
Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli
Set Functions for Time Series
Max Horn, Michael Moor, Christian Bock et al.
Sets Clustering
Ibrahim Jubran, Murad Tukan, Alaa Maalouf et al.
SGD Learns One-Layer Networks in WGANs
Qi Lei, Jason Lee, Alex Dimakis et al.
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion
Qinqing Zheng, Jinshuo Dong, Qi Long et al.
Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification
Chen Dan, Yuting Wei, Pradeep Ravikumar
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
Bo Han, Gang Niu, Xingrui Yu et al.
SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification
Tomer Golany, Kira Radinsky, Daniel Freedman
Simple and Deep Graph Convolutional Networks
Ming Chen, Zhewei Wei, Zengfeng Huang et al.
Simple and sharp analysis of k-means||
Václav Rozhoň
Simultaneous Inference for Massive Data: Distributed Bootstrap
Yang Yu, Shih-Kang Chao, Guang Cheng
Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
Vitchyr Pong, Murtaza Dalal, Steven Lin et al.
Small Data, Big Decisions: Model Selection in the Small-Data Regime
Jorg Bornschein, Francesco Visin, Simon Osindero
Smaller, more accurate regression forests using tree alternating optimization
Arman Zharmagambetov, Miguel Carreira-Perpinan
Small-GAN: Speeding up GAN Training using Core-Sets
Samarth Sinha, Han Zhang, Anirudh Goyal et al.
SoftSort: A Continuous Relaxation for the argsort Operator
Sebastian Prillo, Julian Eisenschlos