Papers
Statistical Inference for Cluster Trees
Jisu KIM, Yen-Chi Chen, Sivaraman Balakrishnan et al.
Statistical Inference for Pairwise Graphical Models Using Score Matching
Ming Yu, Mladen Kolar, Varun Gupta
Statistical Matching of Discrete Data by Bayesian Networks
Eva Endres, Thomas Augustin
Statistical Modeling of Speaker’s Voice with Temporal Co-Location for Active Voice Authentication
Zhong Meng, Biing-Hwang Juang
STCT: Sequentially Training Convolutional Networks for Visual Tracking
Lijun Wang, Wanli Ouyang, Xiaogang Wang et al.
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm
Qiang Liu, Dilin Wang
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches
Jure Žbontar, Yann LeCun
Stereo Matching With Color and Monochrome Cameras in Low-Light Conditions
Hae-Gon Jeon, Joon-Young Lee, Sunghoon Im et al.
Still not there? Comparing Traditional Sequence-to-Sequence Models to Encoder-Decoder Neural Networks on Monotone String Translation Tasks
Carsten Schnober, Steffen Eger, Erik-Lân Do Dinh et al.
Stimulated Deep Neural Network for Speech Recognition
Chunyang Wu, Penny Karanasou, Mark J.F. Gales et al.
Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues
Nihar Shah, Sivaraman Balakrishnan, Aditya Guntuboyina et al.
Stochastic Block BFGS: Squeezing More Curvature out of Data
Robert Gower, Donald Goldfarb, Peter Richtarik
Stochastic Discrete Clenshaw-Curtis Quadrature
Nico Piatkowski, Katharina Morik
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 Neural Networks with Monotonic Activation Functions
Siamak Ravanbakhsh, Barnabas Poczos, Jeff Schneider 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 Optimization for Multiview Representation Learning using Partial Least Squares
Raman Arora, Poorya Mianjy, Teodor Marinov
Stochastic Quasi-Newton Langevin Monte Carlo
Umut Simsekli, Roland Badeau, Taylan Cemgil et al.
Stochastic Structured Prediction under Bandit Feedback
Artem Sokolov, Julia Kreutzer, Stefan Riezler et al.