Support vector machine

Results: 2011



#Item
21Artificial intelligence / Probability / Statistics / Bayesian statistics / Markov networks / Graphical models / Markov random field / Probability theory / Image segmentation / Probabilistic soft logic / Activity recognition / Support vector machine

Collective Activity Detection using Hinge-loss Markov Random Fields Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry Davis University of Maryland College Park, MD 20742 {blondon,sameh,bach,bert,g

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Source URL: psl.umiacs.umd.edu

Language: English - Date: 2013-06-14 19:26:52
22Statistics / Statistical classification / Learning / Machine learning / Support vector machine / Data mining / Polynomial kernel / Feature selection / Linear separability / Receiver operating characteristic / Linear discriminant analysis / Least squares support vector machine

ABOUT MANUSCRIPTS FOR IJ ITA

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Source URL: foibg.com

Language: English - Date: 2015-02-02 08:46:59
23Algebra / Mathematics / Vectors / Statistical classification / Linear algebra / Mathematical optimization / Vector calculus / Support vector machine / Linear separability / Vector space / KarushKuhnTucker conditions / Euclidean vector

Support Vector Machine The Linearly Non-Separable Case Ling Zhu Fall 2013

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Source URL: www.pstat.ucsb.edu

Language: English - Date: 2014-11-07 15:19:49
24Machine learning / Artificial intelligence / Statistical classification / Learning / Ensemble learning / Cybernetics / Boosting / Support vector machine / Linear classifier / Naive Bayes classifier / Online machine learning / Generalization error

A Few Useful Things to Know about Machine Learning Pedro Domingos Department of Computer Science and Engineering University of Washington Seattle, WA, U.S.A.

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Source URL: homes.cs.washington.edu

Language: English - Date: 2015-08-13 22:08:12
25Graph theory / Mathematics / Graph / Matching / Ear decomposition / Support vector machine / Random walk / Line graph / Kernel method

This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOITPAMI, IEEE T

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Source URL: www2.ece.ohio-state.edu

Language: English - Date: 2016-03-04 15:36:09
26Machine learning / Microarrays / Statistical classification / Biology / Statistics / Support vector machine / Polynomial kernel / Affymetrix / Linear classifier / DNA microarray / Kernel method / Gene expression profiling

264 Genome Informatics 13: 264–Characteristics of Support Vector Machines in Gene Expression Analysis

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Source URL: www.jsbi.org

Language: English - Date: 2002-12-19 23:03:34
27Statistical classification / Multi-label classification / Classifier chains / Support vector machine / Naive Bayes classifier / Classification / Cognition

Streaming Multi-label Classification Jesse Read† , Albert Bifet, Geoff Holmes, Bernhard Pfahringer University of Waikato, Hamilton, New Zealand †

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Source URL: users.ics.aalto.fi

Language: English - Date: 2011-10-17 14:24:14
28Statistical classification / Machine learning / Learning / Artificial intelligence / Support vector machine / Polynomial kernel / LIBSVM / Quadratic / Classifier / XTR / Least squares support vector machine

PDF Document

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Source URL: www.work.caltech.edu

Language: English - Date: 2015-01-01 11:20:46
29Artificial neural networks / Artificial intelligence / Learning / Applied mathematics / Recurrent neural network / Long short-term memory / Sepp Hochreiter / Backpropagation / Vanishing gradient problem / Supervised learning / Support vector machine / Generalization error

Optimal Gradient-Based Learning Using Importance Weights Sepp Hochreiter and Klaus Obermayer Bernstein Center for Computational Neuroscience and Technische Universit¨at Berlin

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Source URL: www.bioinf.jku.at

Language: English - Date: 2013-01-23 02:39:45
30Algebra / Mathematics / Statistical classification / Support vector machine / Valuation / Basis / Constructible universe / Isotope lists /  73-96 / Approximately finite-dimensional C*-algebra

Feature Selection and Classification on Matrix Data: From Large Margins To Small Covering Numbers Sepp Hochreiter and Klaus Obermayer Department of Electrical Engineering and Computer Science

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Source URL: www.bioinf.jku.at

Language: English - Date: 2011-08-11 02:12:59
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