Papers
Stochastic Gradient Geodesic MCMC Methods
Chang Liu, Jun Zhu, Yang Song
Stochastic Gradient MCMC with Stale Gradients
Changyou Chen, Nan Ding, Chunyuan Li et al.
Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences
Hongseok Namkoong, John C. Duchi
Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo
Alain Durmus, Umut Simsekli, Eric Moulines et al.
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles
Stefan Lee, Senthil Purushwalkam Shiva Prakash, Michael Cogswell et al.
Stochastic Online AUC Maximization
Yiming Ying, Longyin Wen, Siwei Lyu
Stochastic Optimization for Large-scale Optimal Transport
Aude Genevay, Marco Cuturi, Gabriel Peyré et al.
Stochastic Structured Prediction under Bandit Feedback
Artem Sokolov, Julia Kreutzer, Stefan Riezler et al.
Stochastic Three-Composite Convex Minimization
Alp Yurtsever, Bang Cong Vu, Volkan Cevher
Stochastic Variance Reduction Methods for Saddle-Point Problems
Balamurugan Palaniappan, Francis Bach
Stochastic Variational Deep Kernel Learning
Andrew G Wilson, Zhiting Hu, Ruslan Salakhutdinov et al.
Strategic Attentive Writer for Learning Macro-Actions
Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero et al.
Structure-Blind Signal Recovery
Dmitry Ostrovsky, Zaid Harchaoui, Anatoli Juditsky et al.
Structured Matrix Recovery via the Generalized Dantzig Selector
Sheng Chen, Arindam Banerjee
Structured Prediction Theory Based on Factor Graph Complexity
Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri et al.
Structured Sparse Regression via Greedy Hard Thresholding
Prateek Jain, Nikhil Rao, Inderjit S Dhillon
Sublinear Time Orthogonal Tensor Decomposition
Zhao Song, David Woodruff, Huan Zhang
Sub-sampled Newton Methods with Non-uniform Sampling
Peng Xu, Jiyan Yang, Fred Roosta et al.
Supervised learning through the lens of compression
Ofir David, Shay Moran, Amir Yehudayoff
Supervised Learning with Tensor Networks
Edwin Stoudenmire, David J Schwab
Supervised Word Mover's Distance
Gao Huang, Chuan Guo, Matt J Kusner et al.
SURGE: Surface Regularized Geometry Estimation from a Single Image
Peng Wang, Xiaohui Shen, Bryan Russell et al.
Swapout: Learning an ensemble of deep architectures
Saurabh Singh, Derek Hoiem, David Forsyth
Synthesis of MCMC and Belief Propagation
Sung-Soo Ahn, Michael Chertkov, Jinwoo Shin
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Anh Nguyen, Alexey Dosovitskiy, Jason Yosinski et al.