Papers
Saliency Transfer: An Example-Based Method for Salient Object Detection
Xin Li, Fan Yang, Leiting Chen et al.
Saliency Unified: A Deep Architecture for Simultaneous Eye Fixation Prediction and Salient Object Segmentation
Srinivas S. S. Kruthiventi, Vennela Gudisa, Jaley H. Dholakiya et al.
Sample and Filter: Nonparametric Scene Parsing via Efficient Filtering
Mohammad Najafi, Sarah Taghavi Namin, Mathieu Salzmann et al.
Sample Complexity of Automated Mechanism Design
Maria-Florina F Balcan, Tuomas Sandholm, Ellen Vitercik
Sample-Specific SVM Learning for Person Re-Identification
Ying Zhang, Baohua Li, Huchuan Lu et al.
Sampling-Based Belief Revision
Michael Thielscher
Sampling for Bayesian Program Learning
Kevin Ellis, Armando Solar-Lezama, Josh Tenenbaum
Samsung Poland NLP Team at SemEval-2016 Task 1: Necessity for diversity; combining recursive autoencoders, WordNet and ensemble methods to measure semantic similarity.
Barbara Rychalska, Katarzyna Pakulska, Krystyna Chodorowska et al.
Satisfying Real-world Goals with Dataset Constraints
Gabriel Goh, Andrew Cotter, Maya Gupta et al.
Says Who…? Identification of Expert versus Layman Critics’ Reviews of Documentary Films
Ming Jiang, Jana Diesner
Scalable Adaptive Stochastic Optimization Using Random Projections
Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher et al.
Scalable and Private Media Consumption with Popcorn
Trinabh Gupta, Natacha Crooks, Whitney Mulhern et al.
2016
NSDI
Scalable and Sound Low-Rank Tensor Learning
Hao Cheng, Yaoliang Yu, Xinhua Zhang et al.
Scalable Discrete Sampling as a Multi-Armed Bandit Problem
Yutian Chen, Zoubin Ghahramani
Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation
Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar
Scalable Gaussian Process Classification via Expectation Propagation
Daniel Hernandez-Lobato, Jose Miguel Hernandez-Lobato
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces
William Herlands, Andrew Wilson, Hannes Nickisch et al.
Scalable geometric density estimation
Ye Wang, Antonio Canale, David Dunson
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Jelena Luketina, Mathias Berglund, Klaus Greff et al.
Scalable Greedy Algorithms for Task/Resource Constrained Multi-Agent Stochastic Planning
Pritee Agrawal, Pradeep Varakantham, William Yeoh
Scalable Learning of Bayesian Network Classifiers
Ana M. Martínez, Geoffrey I. Webb, Shenglei Chen et al.
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach
Darı́o Ramos-López, Antonio Salmerón, Rafel Rumı́ et al.
Scalable MCMC for Mixed Membership Stochastic Blockmodels
Wenzhe Li, Sungjin Ahn, Max Welling