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Linear classifier
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351	Noname manuscript No. (will be inserted by the editor) Linear classifiers are nearly optimal when hidden variables have diverse effects Add to Reading List Source URL: www.phillong.info Language: English - Date: 2013-08-07 11:59:18 Statistical classification Machine learning Conditional independence Independence Linear classifier Variance Statistics Probability theory Statistical dependence
352	Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions Philip M. Long Google Mountain View, CA Add to Reading List Source URL: www.phillong.info Language: English - Date: 2013-08-07 12:07:38 Boosting Perceptron Distribution LPBoost Margin classifier Machine learning Ensemble learning AdaBoost
353	Learning Convolutional Feature Hierarchies for Visual Recognition Koray Kavukcuoglu1 , Pierre Sermanet1 , Y-Lan Boureau2,1 , Karol Gregor1 , Micha¨el Mathieu1 , Yann LeCun1 1 Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-10-24 15:10:40 Statistical classification Error detection and correction Yann LeCun Linear classifier Matching pursuit Supervised learning Unsupervised learning Caltech 101 Support vector machine Statistics Artificial intelligence Machine learning
354	In Advances in Neural Information Processing Systems (NIPS), MIT Press, Dec[removed]Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree Daphna Weinshall1 Add to Reading List Source URL: www.cs.huji.ac.il Language: English - Date: 2008-11-10 10:06:16 Parts of speech Classifier Supervised learning Probability Support vector machine Kullback–Leibler divergence Language model Linear classifier Classification rule Statistics Machine learning Statistical classification
355	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 35, NO. 8, AUGUST 2013 Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-10-24 15:08:44 Computer graphics Statistics Segmentation Pattern recognition Feature Pixel Linear classifier Image gradient Image processing Computer vision Imaging
356	SUPERVISED DICTIONARY LEARNING By Add to Reading List Source URL: ima.umn.edu Language: English - Date: 2011-10-06 10:33:16 Statistical theory Statistical models Linear classifier Fisher kernel Discriminative model Supervised learning Maximum likelihood Generative model Dimensional analysis Statistics Machine learning Statistical classification
357	Chunking with Support Vector Machines Taku Kudo and Yuji Matsumoto Graduate School of Information Science, Add to Reading List Source URL: chasen.org Language: English - Date: 2002-01-12 17:42:20 Chunking Margin classifier VC dimension Machine learning Memory Natural language processing Supervised learning Linear classifier Statistics Statistical classification Support vector machine
358	Supervised learning for computer vision: Theory and algorithms - Part I Francis Bach1 & Jean-Yves Audibert2,1 Add to Reading List Source URL: www.di.ens.fr Language: English - Date: 2008-10-11 18:22:01 Supervised learning Empirical risk minimization Support vector machine PP Statistical classification Function Pattern recognition Linear classifier Statistics Machine learning Mathematics
359	Greg Grudic Machine Learning Add to Reading List Source URL: www.cs.colorado.edu Language: English - Date: 2004-01-15 14:43:50 Supervised learning Training set Regression analysis Linear classifier Pattern recognition Statistics Machine learning Learning
360	Machine Learning Greg Grudic Add to Reading List Source URL: www.cs.colorado.edu Language: English - Date: 2004-04-27 15:30:34 Supervised learning Training set Support vector machine Regression analysis Statistical classification Boosting Linear classifier Pattern recognition Statistics Machine learning Artificial intelligence

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