Papers
Soft Threshold Weight Reparameterization for Learnable Sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani et al.
Source Separation with Deep Generative Priors
Vivek Jayaram, John Thickstun
Sparse Convex Optimization via Adaptively Regularized Hard Thresholding
Kyriakos Axiotis, Maxim Sviridenko
Sparse Gaussian Processes with Spherical Harmonic Features
Vincent Dutordoir, Nicolas Durrande, James Hensman
Sparse Shrunk Additive Models
Guodong Liu, Hong Chen, Heng Huang
Sparse Sinkhorn Attention
Yi Tay, Dara Bahri, Liu Yang et al.
Sparse Subspace Clustering with Entropy-Norm
Liang Bai, Jiye Liang
Sparsified Linear Programming for Zero-Sum Equilibrium Finding
Brian Zhang, Tuomas Sandholm
Spectral Clustering with Graph Neural Networks for Graph Pooling
Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi
Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence
Lijun Ding, Yingjie Fei, Qiantong Xu et al.
Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory
Zhou Fan, Cheng Mao, Yihong Wu et al.
Spectral Subsampling MCMC for Stationary Time Series
Robert Salomone, Matias Quiroz, Robert Kohn et al.
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan
Spread Divergence
Mingtian Zhang, Peter Hayes, Thomas Bird et al.
Stabilizing Differentiable Architecture Search via Perturbation-based Regularization
Xiangning Chen, Cho-Jui Hsieh
Stabilizing Transformers for Reinforcement Learning
Emilio Parisotto, Francis Song, Jack Rae et al.
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
William Wilkinson, Paul Chang, Michael Andersen et al.
Statistically Efficient Off-Policy Policy Gradients
Nathan Kallus, Masatoshi Uehara
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck et al.
Stochastically Dominant Distributional Reinforcement Learning
John Martin, Michal Lyskawinski, Xiaohu Li et al.
Stochastic bandits with arm-dependent delays
Manegueu Anne Gael, Claire Vernade, Alexandra Carpentier et al.
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization
Sudeep Salgia, Qing Zhao, Sattar Vakili
Stochastic Differential Equations with Variational Wishart Diffusions
Martin Jørgensen, Marc Deisenroth, Hugh Salimbeni
Stochastic Flows and Geometric Optimization on the Orthogonal Group
Krzysztof Choromanski, David Cheikhi, Jared Davis et al.
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization
Geoffrey Negiar, Gideon Dresdner, Alicia Tsai et al.