Blake A Hunter* (), UCLA Mathematics Department, Box, Los Angeles, CASocial Network Clustering of Sparse Data. Trillions of devices around the world are continuo

Source URL: jointmathematicsmeetings.org

Inspector/Executor Load Balancing Algorithms for Block-Sparse Tensor Contractions 1 Ozog , 2 Hammond ,

Source URL: nic.uoregon.edu

• Computing
• Parallel computing
• NWChem
• Load balancing
• Multi-core processor
• Partition
• Computer cluster

3-D Reconstruction from Sparse Views using Monocular Vision Ashutosh Saxena, Min Sun and Andrew Y. Ng Computer Science Department, Stanford University, Stanford, CA 94305 {asaxena,aliensun,ang}@cs.stanford.edu Abstract

Source URL: ai.stanford.edu

Low-overhead Load-balanced Scheduling for Sparse Tensor Computations

Source URL: www.ieee-hpec.org

CALL FOR PAPERS International Journal on Computer Vision Special Issue on Sparse Coding Aims and Scope Sparse models have gained a tremendous success during the last years in various scientific fields. In statistics and

Source URL: lear.inrialpes.fr

On Noise-Tolerant Learning of Sparse Parities and Related Problems Elena Grigorescu? , Lev Reyzin?? , and Santosh Vempala? ? ? School of Computer Science Georgia Institute of Technology 266 Ferst Drive, Atlanta GA 30332

Source URL: www.levreyzin.com

• Analysis of algorithms
• Computational complexity theory
• Time complexity
• Parity problem
• Parity

On Boosting Sparse Parities Lev Reyzin Department of Mathematics, Statistics, & Computer Science University of Illinois at Chicago Chicago, IL 60607

Source URL: www.levreyzin.com

• Ensemble learning
• AdaBoost
• Boosting
• BrownBoost
• LPBoost
• Decision stump
• LogitBoost
• Support vector machine
• Machine learning
• Supervised learning
• Parity
• Online machine learning

Estimator for Number of Sources using Minimum Description Length Criterion for Blind Sparse Source Mixtures Radu Balan Siemens Corporate Research 755 College Road East

Source URL: www.math.umd.edu

Sparse Online Learning via Truncated Gradient: Appendix 1 Proof of Main Results In the setting of standard online learning, we are interested in sequential prediction problems where

Source URL: hunch.net

• Statistical theory
• Symbol
• Loss function