Turbo-SMT: Accelerating Coupled Sparse Matrix-Tensor Factorizations by 200x - Supplementary Material Evangelos E. Papalexakis∗ Christos Faloutsos ∗

Source URL: talukdar.net

Provable De-anonymization of Large Datasets with Sparse Dimensions Anupam Datta, Divya Sharma, and Arunesh Sinha Carnegie Mellon University {danupam,divyasharma,aruneshs}@cmu.edu

Source URL: www.andrew.cmu.edu

• Anonymity
• Privacy
• Theoretical computer science
• Auxy
• Cryptography
• De-anonymization
• Differential privacy
• Recommender system
• Algorithm
• Academia

Human Action Recognition by Learning Bases of Action Attributes and Parts Bangpeng Yao1 , Xiaoye Jiang2 , Aditya Khosla1 , Andy Lai Lin3 , Leonidas Guibas1 , and Li Fei-Fei1 1 2

Source URL: geometry.stanford.edu

• Science and technology
• Mathematics
• Conference on Computer Vision and Pattern Recognition
• Academia
• Sparse approximation
• Attribute
• Machine learning
• Outline of object recognition
• Compressed sensing

CHROMATIC THRESHOLDS IN SPARSE RANDOM GRAPHS arXiv:1508.03875v1 [math.CO] 16 Aug 2015 ¨ PETER ALLEN, JULIA BOTTCHER,

Source URL: arxiv.org

SOS Lecture 4: Finding planted sparse vector and dictionary learning / Boaz Barak Based on scribed (and greatly expanded) notes by Samuel Hopkins and Jerry Li Finding Sparse Planted Vector 1

Source URL: www.boazbarak.org

Recent  Developments  in  the   Sparse  Fourier  Transform   Piotr  Indyk   MIT   Joint  work  with  Fadel  Adib,  Badih  Ghazi,  Haitham  Hassanieh,  Michael  

Source URL: people.csail.mit.edu

Program Transformations for Automatically Tailoring Algorithms to Sparse Matrices1 Stephen Fitzpatrick, T.J. Harmer, J.M. Boyley , fS.Fitzpatrick, The Queen’s University of Belfa

Source URL: www.kestrel.edu

An introduction to the analysis and implementation of sparse grid finite element methods Stephen Russell · Niall Madden October, 2015 Abstract Our goal is to present an elementary approach to the analysis and pro-

Source URL: www.maths.nuigalway.ie

Application of Automatic Language and Subject Identification for Universal Digital Library using Sparse Data Lavanya Prahallad, Suryakanth V Gangashetty, Kishore Prahallad and Raj Reddy School of Computer Science Carnegi

Source URL: ravi.iiit.ac.in

Modelling local and global phenomena with sparse Gaussian processes Jarno Vanhatalo Department of Biomedical Engineering and Computational Science

Source URL: uai2008.cs.helsinki.fi