Papers
Salt: Combining ACID and BASE in a Distributed Database
Chao Xie, Chunzhi Su, Manos Kapritsos et al.
2014
OSDI
SAMC: Semantic-Aware Model Checking for Fast Discovery of Deep Bugs in Cloud Systems
Tanakorn Leesatapornwongsa, Mingzhe Hao, Pallavi Joshi et al.
2014
OSDI
Sample-based approximate regularization
Philip Bachman, Amir-Massoud Farahmand, Doina Precup
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity
Vitaly Feldman, David Xiao
Sample Compression for Multi-label Concept Classes
Rahim Samei, Pavel Semukhin, Boting Yang et al.
Sample Distillation for Object Detection and Image Classification
Olivier Canevet, Leonidas Lefakis, Francois Fleuret
Sample Efficient Reinforcement Learning with Gaussian Processes
Robert Grande, Thomas Walsh, Jonathan How
Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature
Tom Gunter, Michael A Osborne, Roman Garnett et al.
Sanskrit Linguistics Web Services
Gérard Huet, Amba Kulkarni
SAP-RI: A Constrained and Supervised Approach for Aspect-Based Sentiment Analysis
Naveen Nandan, Daniel Dahlmeier, Akriti Vij et al.
SAP-RI: Twitter Sentiment Analysis in Two Days
Akriti Vij, Nishta Malhotra, Naveen Nandan et al.
Sarcasm Detection on Czech and English Twitter
Tomáš Ptáček, Ivan Habernal, Jun Hong
SA-UZH: Verb-based Sentiment Analysis
Nora Hollenstein, Michael Amsler, Martina Bachmann et al.
Scalable 3D Tracking of Multiple Interacting Objects
Nikolaos Kyriazis, Antonis Argyros
Scalable and Robust Bayesian Inference via the Median Posterior
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin et al.
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
Piyush Rai, Yingjian Wang, Shengbo Guo et al.
Scalable Collaborative Bayesian Preference Learning
Mohammad Emtiyaz Khan, Young Jun Ko, Matthias Seeger
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications
Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin et al.
Scalable Inference for Neuronal Connectivity from Calcium Imaging
Alyson K. Fletcher, Sundeep Rangan
Scalable Kernel Methods via Doubly Stochastic Gradients
Bo Dai, Bo Xie, Niao He et al.
Scalable Large-Margin Structured Learning: Theory and Algorithms
Liang Huang, Kai Zhao, Lemao Liu
Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices
Austin R Benson, Jason Lee, Bartek Rajwa et al.
Scalable Multitask Representation Learning for Scene Classification
Maksim Lapin, Bernt Schiele, Matthias Hein
Scalable Non-linear Learning with Adaptive Polynomial Expansions
Alekh Agarwal, Alina Beygelzimer, Daniel J. Hsu et al.
Scalable Object Detection using Deep Neural Networks
Dumitru Erhan, Christian Szegedy, Alexander Toshev et al.