Papers
4,122 papers found
Scalable High-Dimensional Multivariate Linear Regression for Feature-Distributed Data
Shuo-Chieh Huang, Ruey S. Tsay
Scalable Resampling in Massive Generalized Linear Models via Subsampled Residual Bootstrap
Indrila Ganguly, Srijan Sengupta, Sujit Ghosh
Scaled Conjugate Gradient Method for Nonconvex Optimization in Deep Neural Networks
Naoki Sato, Koshiro Izumi, Hideaki Iiduka
Scaling Instruction-Finetuned Language Models
Hyung Won Chung, Le Hou, Shayne Longpre et al.
Scaling Speech Technology to 1,000+ Languages
Vineel Pratap, Andros Tjandra, Bowen Shi et al.
Scaling the Convex Barrier with Sparse Dual Algorithms
Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel et al.
Seeded Graph Matching for the Correlated Gaussian Wigner Model via the Projected Power Method
Ernesto Araya, Guillaume Braun, Hemant Tyagi
Semi-supervised Inference for Block-wise Missing Data without Imputation
Shanshan Song, Yuanyuan Lin, Yong Zhou
Sharp analysis of power iteration for tensor PCA
Yuchen Wu, Kangjie Zhou
Sharpness-Aware Minimization and the Edge of Stability
Philip M. Long, Peter L. Bartlett
Simple Cycle Reservoirs are Universal
Boyu Li, Robert Simon Fong, Peter Tino
skscope: Fast Sparsity-Constrained Optimization in Python
Zezhi Wang, Junxian Zhu, Xueqin Wang et al.
Sparse Graphical Linear Dynamical Systems
Emilie Chouzenoux, Victor Elvira
Sparse NMF with Archetypal Regularization: Computational and Robustness Properties
Kayhan Behdin, Rahul Mazumder
Sparse Recovery With Multiple Data Streams: An Adaptive Sequential Testing Approach
Weinan Wang, Bowen Gang, Wenguang Sun
Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces
Rui Wang, Yuesheng Xu, Mingsong Yan
Spatial meshing for general Bayesian multivariate models
Michele Peruzzi, David B. Dunson
Spectral Analysis of the Neural Tangent Kernel for Deep Residual Networks
Yuval Belfer, Amnon Geifman, Meirav Galun et al.
Spectral learning of multivariate extremes
Marco Avella Medina, Richard A Davis, Gennady Samorodnitsky
Spectral Regularized Kernel Goodness-of-Fit Tests
Omar Hagrass, Bharath K. Sriperumbudur, Bing Li
Spherical Rotation Dimension Reduction with Geometric Loss Functions
Hengrui Luo, Jeremy E. Purvis, Didong Li
Split Conformal Prediction and Non-Exchangeable Data
Roberto I. Oliveira, Paulo Orenstein, Thiago Ramos et al.
Stability and L2-penalty in Model Averaging
Hengkun Zhu, Guohua Zou
Stable and Consistent Density-Based Clustering via Multiparameter Persistence
Alexander Rolle, Luis Scoccola
Stable Implementation of Probabilistic ODE Solvers
Nicholas Krämer, Philipp Hennig