Papers
Sample Efficient Policy Search for Optimal Stopping Domains
Karan Goel, Christoph Dann, Emma Brunskill
Sampling-Based Speech Parameter Generation Using Moment-Matching Networks
Shinnosuke Takamichi, Tomoki Koriyama, Hiroshi Saruwatari
Sampling for Approximate Maximum Search in Factorized Tensor
Zhi Lu, Yang Hu, Bing Zeng
Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo
Nicolas Brosse, Alain Durmus, Éric Moulines et al.
Sampling Matters in Deep Embedding Learning
Chao-Yuan Wu, R. Manmatha, Alexander J. Smola et al.
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M. Nguyen, Jie Liu, Katya Scheinberg et al.
Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translation
Lotem Peled, Roi Reichart
Satirical News Detection and Analysis using Attention Mechanism and Linguistic Features
Fan Yang, Arjun Mukherjee, Eduard Dragut
SBGAR: Semantics Based Group Activity Recognition
Xin Li, Mooi Choo Chuah
SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning
Long Chen, Hanwang Zhang, Jun Xiao et al.
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling
Zhe Gan, Chunyuan Li, Changyou Chen et al.
Scalable Bayesian Rule Lists
Hongyu Yang, Cynthia Rudin, Margo Seltzer
Scalable Constraint-based Virtual Data Center Allocation
Sam Bayless, Nodir Kodirov, Ivan Beschastnikh et al.
Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition
Jiong Zhang, Ian En-Hsu Yen, Pradeep Ravikumar et al.
Scalable Demand-Aware Recommendation
Jinfeng Yi, Cho-Jui Hsieh, Kush R Varshney et al.
Scalable Estimation of Dirichlet Process Mixture Models on Distributed Data
Ruohui Wang, Dahua Lin
Scalable Generalized Linear Bandits: Online Computation and Hashing
Kwang-Sung Jun, Aniruddha Bhargava, Robert Nowak et al.
Scalable Generative Models for Multi-label Learning with Missing Labels
Vikas Jain, Nirbhay Modhe, Piyush Rai
Scalable Greedy Feature Selection via Weak Submodularity
Rajiv Khanna, Ethan Elenberg, Alex Dimakis et al.
Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks
Nan Du, Yingyu Liang, Maria-Florina Balcan et al.
Scalable Learning of Non-Decomposable Objectives
Elad Eban, Mariano Schain, Alan Mackey et al.
Scalable Levy Process Priors for Spectral Kernel Learning
Phillip A Jang, Andrew Loeb, Matthew Davidow et al.
Scalable Log Determinants for Gaussian Process Kernel Learning
Kun Dong, David Eriksson, Hannes Nickisch et al.
Scalable Model Selection for Belief Networks
Zhao Song, Yusuke Muraoka, Ryohei Fujimaki et al.