Papers
Scalable Semi-Supervised Query Classification Using Matrix Sketching
Young-Bum Kim, Karl Stratos, Ruhi Sarikaya
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit
Chong You, Daniel Robinson, Rene Vidal
Scalable Statistical Relational Learning for NLP
William Yang Wang, William Cohen
Scalable Structure Discovery in Regression using Gaussian Processes
Hyunjik Kim, Yee Whye Teh
Scale-Adaptive Low-Resolution Person Re-Identification via Learning a Discriminating Surface
Zheng Wang, Ruimin Hu, Yi Yu et al.
Scale-Aware Alignment of Hierarchical Image Segmentation
Yuhua Chen, Dengxin Dai, Jordi Pont-Tuset et al.
Scaled Least Squares Estimator for GLMs in Large-Scale Problems
Murat A Erdogdu, Lee H Dicker, Mohsen Bayati
Scaling a Natural Language Generation System
Jonathan Pfeil, Soumya Ray
Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages
Yin Cheng Ng, Pawel M Chilinski, Ricardo Silva
Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes
Jack Rae, Jonathan J Hunt, Ivo Danihelka et al.
Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics
Stephan Clémençon, Igor Colin, Aurélien Bellet
Scaling Up Word Clustering
Jon Dehdari, Liling Tan, Josef van Genabith
Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much
Bryan D He, Christopher M De Sa, Ioannis Mitliagkas et al.
Scene Labeling Using Sparse Precision Matrix
Nasim Souly, Mubarak Shah
Scene Recognition With CNNs: Objects, Scales and Dataset Bias
Luis Herranz, Shuqiang Jiang, Xiangyang Li
Scene Text Detection in Video by Learning Locally and Globally
Shu Tian, Wei-Yi Pei, Ze-Yu Zuo et al.
Science Question Answering using Instructional Materials
Mrinmaya Sachan, Kumar Dubey, Eric Xing
SCONE: Secure Linux Containers with Intel SGX
Sergei Arnautov, Bohdan Trach, Franz Gregor et al.
ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation
Di Lin, Jifeng Dai, Jiaya Jia et al.
SDCA without Duality, Regularization, and Individual Convexity
Shai Shalev-Shwartz
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization
Zheng Qu, Peter Richtarik, Martin Takac et al.
SDP Relaxation with Randomized Rounding for Energy Disaggregation
Kiarash Shaloudegi, András György, Csaba Szepesvari et al.