Papers
Score Matched Neural Exponential Families for Likelihood-Free Inference
Lorenzo Pacchiardi, Ritabrata Dutta
Selective Machine Learning of the Average Treatment Effect with an Invalid Instrumental Variable
Baoluo Sun, Yifan Cui, Eric Tchetgen Tchetgen
Self-Healing Robust Neural Networks via Closed-Loop Control
Zhuotong Chen, Qianxiao Li, Zheng Zhang
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables
Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser
SGD with Coordinate Sampling: Theory and Practice
Rémi Leluc, François Portier
Signature Moments to Characterize Laws of Stochastic Processes
Ilya Chevyrev, Harald Oberhauser
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States
Shi Dong, Benjamin Van Roy, Zhengyuan Zhou
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
Marius Lindauer, Katharina Eggensperger, Matthias Feurer et al.
Smooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee
Bo Shen, Weijun Xie, Zhenyu (James) Kong
SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks
Weijing Tang, Jiaqi Ma, Qiaozhu Mei et al.
solo-learn: A Library of Self-supervised Methods for Visual Representation Learning
Victor Guilherme Turrisi da Costa, Enrico Fini, Moin Nabi et al.
Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation
Antoine Dedieu, Rahul Mazumder, Haoyue Wang
Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality
Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet
Sparse Additive Gaussian Process Regression
Hengrui Luo, Giovanni Nattino, Matthew T. Pratola
Sparse Continuous Distributions and Fenchel-Young Losses
André F. T. Martins, Marcos Treviso, António Farinhas et al.
Spatial Multivariate Trees for Big Data Bayesian Regression
Michele Peruzzi, David B. Dunson
Stable Classification
Dimitris Bertsimas, Jack Dunn, Ivan Paskov
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors
Yuling Yao, Aki Vehtari, Andrew Gelman
Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA
Nicholas Sterge, Bharath K. Sriperumbudur
Statistical Optimality and Stability of Tangent Transform Algorithms in Logit Models
Indrajit Ghosh, Anirban Bhattacharya, Debdeep Pati
Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification
Yingying Zhang, Yan-Yong Zhao, Heng Lian
Stochastic DCA with Variance Reduction and Applications in Machine Learning
Hoai An Le Thi, Hoang Phuc Hau Luu, Hoai Minh Le et al.
Stochastic subgradient for composite convex optimization with functional constraints
Ion Necoara, Nitesh Kumar Singh
Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity
Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi et al.