Papers
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers
Kiwon Um, Robert Brand, Yun (Raymond) Fei et al.
Space-Time Correspondence as a Contrastive Random Walk
Allan Jabri, Andrew Owens, Alexei Efros
Sparse and Continuous Attention Mechanisms
André Martins, António Farinhas, Marcos Treviso et al.
Sparse Graphical Memory for Robust Planning
Scott Emmons, Ajay N. Jain, Misha Laskin et al.
Sparse Learning with CART
Jason Klusowski
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning
Anthony Tompkins, Rafael Oliveira, Fabio T Ramos
Sparse Symplectically Integrated Neural Networks
Daniel DiPietro, Shiying Xiong, Bo Zhu
Sparse Weight Activation Training
Md Aamir Raihan, Tor Aamodt
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Defu Cao, Yujing Wang, Juanyong Duan et al.
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks
Zhou Fan, Zhichao Wang
Spike and slab variational Bayes for high dimensional logistic regression
Kolyan Ray, Botond Szabo, Gabriel Clara
Spin-Weighted Spherical CNNs
Carlos Esteves, Ameesh Makadia, Kostas Daniilidis
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán et al.
Stable and expressive recurrent vision models
Drew Linsley, Alekh Karkada Ashok, Lakshmi Narasimhan Govindarajan et al.
Stage-wise Conservative Linear Bandits
Ahmadreza Moradipari, Christos Thrampoulidis, Mahnoosh Alizadeh
Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision Processes
Yuval Emek, Ron Lavi, Rad Niazadeh et al.
Stationary Activations for Uncertainty Calibration in Deep Learning
Lassi Meronen, Christabella Irwanto, Arno Solin
Statistical and Topological Properties of Sliced Probability Divergences
Kimia Nadjahi, Alain Durmus, Lénaïc Chizat et al.
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso
Jerome-Alexis Chevalier, Joseph Salmon, Alexandre Gramfort et al.
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits
Pierre Perrault, Etienne Boursier, Michal Valko et al.
Statistical Guarantees of Distributed Nearest Neighbor Classification
Jiexin Duan, Xingye Qiao, Guang Cheng
Statistical Optimal Transport posed as Learning Kernel Embedding
Saketha Nath Jagarlapudi, Pratik Kumar Jawanpuria
Statistical-Query Lower Bounds via Functional Gradients
Surbhi Goel, Aravind Gollakota, Adam Klivans
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction
Benoît Colange, Jaakko Peltonen, Michael Aupetit et al.