Papers
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.
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
Quoc Tran-Dinh, Nhan Pham, Lam Nguyen
Stochastic Gradient and Langevin Processes
Xiang Cheng, Dong Yin, Peter Bartlett et al.
Stochastic Hamiltonian Gradient Methods for Smooth Games
Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau et al.
Stochastic Latent Residual Video Prediction
Jean-Yves Franceschi, Edouard Delasalles, Mickael Chen et al.
Stochastic Optimization for Non-convex Inf-Projection Problems
Yan Yan, Yi Xu, Lijun Zhang et al.
Stochastic Optimization for Regularized Wasserstein Estimators
Marin Ballu, Quentin Berthet, Francis Bach
StochasticRank: Global Optimization of Scale-Free Discrete Functions
Aleksei Ustimenko, Liudmila Prokhorenkova
Stochastic Regret Minimization in Extensive-Form Games
Gabriele Farina, Christian Kroer, Tuomas Sandholm
Stochastic Subspace Cubic Newton Method
Filip Hanzely, Nikita Doikov, Yurii Nesterov et al.
Strategic Classification is Causal Modeling in Disguise
John Miller, Smitha Milli, Moritz Hardt