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Support vector machine
Results: 2011

#	Item
361	Efficient Learning of Mahalanobis Metrics for Ranking Daryl K. H. Lim DKLIM @ UCSD . EDU Department of Electrical and Computer Engineering, University of California, San Diego, CAUSA Gert Lanckriet Add to Reading List Source URL: acsweb.ucsd.edu Language: English - Date: 2014-06-16 18:55:07 Machine learning Learning Statistics Mathematics Learning to rank Support vector machine XQ Valuation Supervised learning Stochastic gradient descent
362	PDF Document Add to Reading List Source URL: egice2014.engineering.cf.ac.uk Language: English - Date: 2014-10-03 12:45:14 Statistics Econometrics Prediction Regression analysis Statistical forecasting Scientific modeling Estimation theory Linear regression Support vector machine Forecasting Time series Economic model
363	Statistical Machine Learning UoC Stats 37700, Winter quarter Lecture 6: Support Vector Machines. Add to Reading List Source URL: users.math.uni-potsdam.de Language: English - Date: 2010-10-28 03:45:49
364	Towards HorizonLasaponara R., Masini N., Biscione M., Editors EARSeL, 2013 Habitat mapping and monitoring in Alpine regions Add to Reading List Source URL: www.earsel.org Language: English - Date: 2014-01-10 12:13:38 Planetary science Cartography RapidEye Space technology Satellite imagery Wetland Support vector machine METRIC Natura Earth Remote sensing Geography
365	Fusing Subcategory Probabilities for Texture Classification Yang Song1 , Weidong Cai1 , Qing Li1 , Fan Zhang1 , David Dagan Feng1 , Heng Huang2 1 BMIT Research Group, School of IT, University of Sydney, Australia 2 Depar Add to Reading List Source URL: www.cv-foundation.org Language: English - Date: 2015-05-25 21:19:09 Support vector machine Statistical classification Category theory Subcategory
366	Food-101 – Mining Discriminative Components with Random Forests Lukas Bossard1 1 Matthieu Guillaumin1 Add to Reading List Source URL: www.vision.ee.ethz.ch Language: English - Date: 2014-07-09 13:23:14 Support vector machine Random forest Statistics Statistical classification Linear classifier
367	Comparison of Classifier Selection Methods for Improving Committee Performance Matti Aksela Helsinki University of Technology, Neural Networks Research Centre P.O.Box 5400, FinHUT, Finland Add to Reading List Source URL: www.cis.hut.fi Language: English - Date: 2006-05-30 07:20:10 Parts of speech Statistical classification Ensemble learning Learning classifier system Classifier Support vector machine Chinese classifier Random subspace method Machine learning Statistics Artificial intelligence
368	An Introduction to Feature Extraction Isabelle Guyon1 and Andr´e Elisseeff2 1 2 ClopiNet, 955 Creston Rd., Berkeley, CA 94708, USA. Add to Reading List Source URL: clopinet.com Language: English - Date: 2006-10-19 12:27:10 Dimension reduction Model selection Computer vision Feature selection Support vector machine Kernel methods Feature extraction Training set Cross-validation Statistics Machine learning Artificial intelligence
369	An Empirical Comparison of Supervised Learning Algorithms Rich Caruana Alexandru Niculescu-Mizil Department of Computer Science, Cornell University, Ithaca, NYUSA Add to Reading List Source URL: www.niculescu-mizil.org Language: English - Date: 2008-11-22 14:04:17 Ensemble learning Bayesian statistics Neural networks Supervised learning Support vector machine Naive Bayes classifier Boosting Random forest Calibration Statistics Machine learning Statistical classification
370	Combining Multi-class SVMs with Linear Ensemble Methods that Estimate the Class Posterior Probabilities Yann Guermeur LORIA-CNRS Campus Scientique, BP 239 Add to Reading List Source URL: www.loria.fr Language: English - Date: 2013-06-20 15:49:31 Statistics Statistical classification Functions and mappings Support vector machine Convex optimization Function Convex function Locally convex topological vector space Least squares support vector machine Convex analysis Mathematical analysis Mathematics

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