arXiv:1405.3564v1 [cond-mat.mtrl-sci] 14 MayAn Investigation of Machine Learning Methods Applied to Structure Prediction in Condensed Matter William J. Brouwer1,a James D. Kubicki,b Jorge O. Sofo,c C. Lee Gilesd a

Source URL: clgiles.ist.psu.edu

• Nuclear magnetic resonance
• Econometrics
• Spectroscopy
• Solid-state nuclear magnetic resonance
• Regression analysis
• Linear regression
• Nuclear magnetic resonance crystallography
• Residual dipolar coupling

De-anonymizing Users Across Heterogeneous Social Computing Platforms Mohammed Korayem and David J. Crandall School of Informatics & Computing, Indiana University, Bloomington, IN, USA 1. Motivation

Source URL: vision.soic.indiana.edu

• Software
• Computing
• Social networking services
• Social media
• Universal Windows Platform apps
• Machine learning
• Statistical classification
• Twitter
• Cosine similarity
• Facebook
• Naive Bayes classifier
• Classifier

Evaluation of Mechanisms for Fine-Grained Parallel Programs in the J-Machine and the CM-5 Ellen Spertusy, Seth Copen Goldsteinz, Klaus Erik Schauserz, Thorsten von Eickenz, David E. Cullerz, William J. Dallyy yMIT Artifi

Source URL: www.cs.cmu.edu

Pires, J. & Dumont, A.G.D 2015_(STRC)

Source URL: www.strc.ch

• Permanent way
• Tribology
• Maintenance of way equipment
• Track ballast
• Tamping machine
• Tamp
• Track
• Fouling
• Railroad tie
• Ballast
• Wear
• Abrasion

Lost in Translation: Improving Decoy Documents via Automated Translation Jonathan Voris, Nathaniel Boggs, and Salvatore J. Stolfo Department of Computer Science Columbia University New York, NY 10027, USA {jvoris,boggs,s

Source URL: ids.cs.columbia.edu

• Computer-assisted translation
• Decoy
• Salvatore J. Stolfo
• Machine translation
• Translation
• Google Translate

A Comparison of Algorithms for Inference and Learning in Probabilistic Graphical Models Brendan J. Frey and Nebojsa Jojic Abstract Computer vision is currently one of the most exciting areas of artificial intelligence re

Source URL: www.isit2004.org

• Statistics
• Statistical models
• Probability
• Graphical models
• Machine learning
• Statistical theory
• Bayesian statistics
• Markov random field
• Bayesian network
• Generative model
• Factor graph
• Discriminative model

Extra opgaven W9 1. We wish to schedule n jobs on m machines. Each job must be processed on each machine, and the machine order is fixed, that is, job j must first me processed on machine j(1), then on machine j(2), and

Source URL: leovaniersel.files.wordpress.com

lishers, New York, Mu90]Muraski, S. J., “Make it in a minute,” Machine Design, February 1990, ppPS85] Preparata, F.P., and M.I. Shamos, Computational Geometry – An Introduction, Springer-Verlag, N

Source URL: www-cgrl.cs.mcgill.ca

Automatically and Efficiently Inferring the Hierarchical Structure of Visual Maps Margarita Chli and Andrew J. Davison Imperial College London, London SW7 2AZ, UK {mchli,ajd}@doc.ic.ac.uk

Source URL: www.margaritachli.com

• Artificial intelligence
• ChowLiu tree
• Knowledge representation
• Mutual information
• Simultaneous localization and mapping
• Pattern recognition
• Machine learning
• Cognition
• Cognitive science

1 Efficient Data Association in Images using Active Matching Margarita Chli and Andrew J. Davison {mchli, ajd}@doc.ic.ac.uk

Source URL: www.margaritachli.com

• Artificial intelligence
• Machine learning
• Video processing
• Image processing
• Signal processing
• Learning
• Template matching
• Outline of object recognition
• Mixture model
• Motion estimation
• Pattern recognition
• Video tracking