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Artificial intelligence
Results: 12164

#	Item
681	On-line Hierarchical Multi-label Text Classification Jesse Read September 7, 2007 On-line Hierarchical Multi-label Text Classification Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2010-10-25 05:10:53 Statistical classification Machine learning Artificial intelligence Learning Statistics Multi-label classification Naive Bayes classifier Classifier AdaBoost Document classification Binary classification Classifier chains
682	Keep, Change or Delete? Setting up a Low Resource OCR Post-correction Framework for a Digitized Old Finnish Newspaper Collection Kimmo Kettunen Center for Preservation and Digitisation, National Library of Finland, Mikke Add to Reading List Source URL: ircdl2015.unibz.it Language: English - Date: 2015-01-24 10:45:42 Artificial intelligence Computational linguistics Evaluation of machine translation Speech recognition Information Statistics Optical character recognition Symbols Unicode Precision and recall Word error rate Error detection and correction
683	MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Data selection by sequence summarizing neural network in mismatch condition training Zmolikova, K.; Karafiat, M.; Vesely, K.; Delcroix, M.; Watanabe, S.; Burg Add to Reading List Source URL: www.merl.com Language: English - Date: 2016-08-01 10:13:57 Machine learning Artificial neural networks Artificial intelligence Applied mathematics Automatic identification and data capture Computer accessibility Speech recognition Boltzmann machine Deep learning
684	The Mind BY NILS J. NILSSON [This essay was published in The Stanford Magazine, pp, Winter, 1986 as part of a feature called “What is the Question?”] Is the mind a machine? If it is and if we could build one, Add to Reading List Source URL: ai.stanford.edu Language: English - Date: 2004-07-12 18:37:42 Cognitive science Cognition Philosophy Philosophy of artificial intelligence Computational neuroscience Philosophy of technology Neuropsychological assessment Mind Artificial intelligence Reason Question Thought
685	TOWARD A SCIENCE OF CONSCIOUSNESS TUCSON CONFERENCE ABSTRACT TAXONOMY 2014 REVISEDPhilosophy Add to Reading List Source URL: www.consciousness.arizona.edu Language: English - Date: 2013-07-24 14:26:42 Cognitive science Neuroscience Psychology Consciousness Cognition Philosophy of mind Artificial intelligence Neural correlates of consciousness Artificial consciousness Hard problem of consciousness Quantum mind Cognitive architecture
686	Multiple Kernel Learning, Conic Duality, and the SMO Algorithm Francis R. Bach & Gert R. G. Lanckriet {fbach,gert}@cs.berkeley.edu Department of Electrical Engineering and Computer Science, University of California, Ber Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:25 Machine learning Learning Support vector machines Artificial intelligence Sequential minimal optimization Multiple kernel learning NC Kernel method KarushKuhnTucker conditions
687	Microsoft Word - IBSS&K Engineering.doc Add to Reading List Source URL: foibg.com Language: English - Date: 2015-02-02 08:46:08 Computing Software engineering Software Inductive reasoning Reasoning Object-oriented programming Case-based reasoning Critical thinking Artificial intelligence Reasoning system Comic book archive CBR
688	Question-Answering Using Semantic Relation Triples Kenneth C. Litkowski CL Research 9208 Gue Road Damascus, MD 20872 Add to Reading List Source URL: www.clres.com Language: English - Date: 2005-03-25 23:00:59 Computational linguistics Linguistics Natural language processing Language Artificial intelligence Grammar Artificial intelligence applications Question answering Parsing Semantic similarity Question Automatic summarization
689	C:/usr/ztu/Document/paper/Journal/2008/cviu/revision/CVIU_horse_submission_SF.dvi Add to Reading List Source URL: pages.ucsd.edu Language: English - Date: 2010-06-26 20:31:07 Feature detection Image processing Artificial intelligence Machine learning Image segmentation Canny edge detector Edge detection Learning Statistics Mixture model
690	Batch-Incremental vs. Instance-Incremental Learning in Dynamic and Evolving Data Jesse Read1 , Albert Bifet2 , Bernhard Pfahringer2 , Geoff Holmes2 1 Department of Signal Theory and Communications Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2012-10-25 03:54:39 Statistics Machine learning Learning Artificial intelligence Statistical classification Data mining Concept drift Massive Online Analysis K-nearest neighbors algorithm Support vector machine Stochastic gradient descent Batch processing

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