Papers
Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random Variables
Yi-Shan Wu, Yevgeny Seldin
SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion
Sheng Yu Huang, Hao-Yu Hsu, Frank Wang
S-Prompts Learning with Pre-trained Transformers: An Occam’s Razor for Domain Incremental Learning
Yabin Wang, Zhiwu Huang, Xiaopeng Hong
SQ Lower Bounds for Learning Single Neurons with Massart Noise
Ilias Diakonikolas, Daniel Kane, Lisheng Ren et al.
Squeezeformer: An Efficient Transformer for Automatic Speech Recognition
Sehoon Kim, Amir Gholami, Albert Shaw et al.
Stability Analysis and Generalization Bounds of Adversarial Training
Jiancong Xiao, Yanbo Fan, Ruoyu Sun et al.
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks
Yunwen Lei, Rong Jin, Yiming Ying
Stability and Generalization for Markov Chain Stochastic Gradient Methods
Puyu Wang, Yunwen Lei, Yiming Ying et al.
Stability and Generalization of Kernel Clustering: from Single Kernel to Multiple Kernel
Weixuan Liang, Xinwang Liu, Yong Liu et al.
ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning
Junting Pan, Ziyi Lin, Xiatian Zhu et al.
Staggered Rollout Designs Enable Causal Inference Under Interference Without Network Knowledge
Mayleen Cortez, Matthew Eichhorn, Christina Yu
Staircase Attention for Recurrent Processing of Sequences
Da JU, Stephen Roller, Sainbayar Sukhbaatar et al.
STaR: Bootstrapping Reasoning With Reasoning
Eric Zelikman, Yuhuai Wu, Jesse Mu et al.
Stars: Tera-Scale Graph Building for Clustering and Learning
CJ Carey, Jonathan Halcrow, Rajesh Jayaram et al.
Star Temporal Classification: Sequence Modeling with Partially Labeled Data
Vineel Pratap, Awni Hannun, Gabriel Synnaeve et al.
Statistical Learning and Inverse Problems: A Stochastic Gradient Approach
Yuri Fonseca, Yuri Saporito
Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers
Colin Wei, Yining Chen, Tengyu Ma
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances
Sloan Nietert, Ziv Goldfeld, Ritwik Sadhu et al.
Stimulative Training of Residual Networks: A Social Psychology Perspective of Loafing
Peng Ye, Shengji Tang, Baopu Li et al.
STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers
Trung Le, Eli Shlizerman
Stochastic Adaptive Activation Function
Kyungsu Lee, Jaeseung Yang, Haeyun Lee et al.
Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions
Xufeng Cai, Chaobing Song, Cristóbal Guzmán et al.
Stochastic Multiple Target Sampling Gradient Descent
Hoang Phan, Ngoc Tran, Trung Le et al.
Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality
Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions
Saeed Masiha, Saber Salehkaleybar, Niao He et al.