Papers
Sampling Algebraic Varieties for Robust Camera Autocalibration
Danda Pani Paudel, Luc Van Gool
Sampling-Based Approximation Algorithms for Reachability Analysis with Provable Guarantees
Lucas Liebenwein, Cenk Baykal, Igor Gilitschenski et al.
Sampling for Approximate Bipartite Network Projection
Nesreen Ahmed, Nick Duffield, Liangzhen Xia
Sampling Informative Training Data for RNN Language Models
Jared Fernandez, Doug Downey
Sampling Strategies in Siamese Networks for Unsupervised Speech Representation Learning
Rachid Riad, Corentin Dancette, Julien Karadayi et al.
Samsung and University of Edinburgh’s System for the IWSLT 2018 Low Resource MT Task
Philip Williams, Marcin Chochowski, Pawel Przybysz et al.
Sanity Checks for Saliency Maps
Julius Adebayo, Justin Gilmer, Michael Muelly et al.
SAN: Learning Relationship between Convolutional Features for Multi-Scale Object Detection
Yonghyun Kim, Bong-Nam Kang, Daijin Kim
Sanskrit n-Retroflexion is Input-Output Tier-Based Strictly Local
Thomas Graf, Connor Mayer
Sanskrit Sandhi Splitting using seq2(seq)2
Rahul Aralikatte, Neelamadhav Gantayat, Naveen Panwar et al.
Sanskrit Word Segmentation Using Character-level Recurrent and Convolutional Neural Networks
Oliver Hellwig, Sebastian Nehrdich
SANTO: A Web-based Annotation Tool for Ontology-driven Slot Filling
Matthias Hartung, Hendrik ter Horst, Frank Grimm et al.
Saturating Splines and Feature Selection
Nicholas Boyd, Trevor Hastie, Stephen Boyd et al.
Saying no but meaning yes: negation and sentiment analysis in Basque
Jon Alkorta, Koldo Gojenola, Mikel Iruskieta
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
Bo Dai, Albert Shaw, Lihong Li et al.
SB@GU at the Complex Word Identification 2018 Shared Task
David Alfter, Ildikó Pilán
SBNet: Sparse Blocks Network for Fast Inference
Mengye Ren, Andrei Pokrovsky, Bin Yang et al.
Scalable and Effective Deep CCA via Soft Decorrelation
Xiaobin Chang, Tao Xiang, Timothy M. Hospedales
Scalable approximate Bayesian inference for particle tracking data
Ruoxi Sun, Liam Paninski
Scalable Bayes via Barycenter in Wasserstein Space
Sanvesh Srivastava, Cheng Li, David B. Dunson
Scalable Bilinear Pi Learning Using State and Action Features
Yichen Chen, Lihong Li, Mengdi Wang
Scalable Construction and Reasoning of Massive Knowledge Bases
Xiang Ren, Nanyun Peng, William Yang Wang
Scalable Coordinated Exploration in Concurrent Reinforcement Learning
Maria Dimakopoulou, Ian Osband, Benjamin Van Roy
Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor et al.