Papers
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations
Qitian Wu, Wentao Zhao, Chenxiao Yang et al.
SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark
Zeyu Zhang, Robert Pless, Nadia Shakoor et al.
SHAP-IQ: Unified Approximation of any-order Shapley Interactions
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki et al.
Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples
Shaokui Wei, Mingda Zhang, Hongyuan Zha et al.
Sharp Bounds for Generalized Causal Sensitivity Analysis
Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel
Sharp Calibrated Gaussian Processes
Alexandre Capone, Sandra Hirche, Geoff Pleiss
Sharpness-Aware Minimization Leads to Low-Rank Features
Maksym Andriushchenko, Dara Bahri, Hossein Mobahi et al.
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization
Kaiyue Wen, Zhiyuan Li, Tengyu Ma
Sharp Recovery Thresholds of Tensor PCA Spectral Algorithms
Michael Feldman, David Donoho
Sharp Spectral Rates for Koopman Operator Learning
Vladimir Kostic, Karim Lounici, Pietro Novelli et al.
Sheaf Hypergraph Networks
Iulia Duta, Giulia Cassarà, Fabrizio Silvestri et al.
SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models
Hongxin Li, Jingran Su, Yuntao Chen et al.
ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
Haoran You, Huihong Shi, Yipin Guo et al.
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
JunHoo Lee, Jayeon Yoo, Nojun Kwak
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
Hammaad Adam, Fan Yin, Huibin Hu et al.
Should Under-parameterized Student Networks Copy or Average Teacher Weights?
Berfin Simsek, Amire Bendjeddou, Wulfram Gerstner et al.
Should We Learn Most Likely Functions or Parameters?
Shikai Qiu, Tim G. J. Rudner, Sanyam Kapoor et al.
Siamese Masked Autoencoders
Agrim Gupta, Jiajun Wu, Jia Deng et al.
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning
Yifan Yang, Peiyao Xiao, Kaiyi Ji
Similarity-based cooperative equilibrium
Caspar Oesterheld, Johannes Treutlein, Roger B Grosse et al.
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities
Aleksandr Beznosikov, Martin Takac, Alexander Gasnikov
SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
Hao Dong, Ismail Nejjar, Han Sun et al.
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
Jiaxiang Dong, Haixu Wu, Haoran Zhang et al.
Simple and Asymmetric Graph Contrastive Learning without Augmentations
Teng Xiao, Huaisheng Zhu, Zhengyu Chen et al.