Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine ... 11-13, 2005, Revised Selected Papers: 3944 - Brossura
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This book constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
Evaluating Predictive Uncertainty Challenge.- Classification with Bayesian Neural Networks.- A Pragmatic Bayesian Approach to Predictive Uncertainty.- Many Are Better Than One: Improving Probabilistic Estimates from Decision Trees.- Estimating Predictive Variances with Kernel Ridge Regression.- Competitive Associative Nets and Cross-Validation for Estimating Predictive Uncertainty on Regression Problems.- Lessons Learned in the Challenge: Making Predictions and Scoring Them.- The 2005 PASCAL Visual Object Classes Challenge.- The PASCAL Recognising Textual Entailment Challenge.- Using Bleu-like Algorithms for the Automatic Recognition of Entailment.- What Syntax Can Contribute in the Entailment Task.- Combining Lexical Resources with Tree Edit Distance for Recognizing Textual Entailment.- Textual Entailment Recognition Based on Dependency Analysis and WordNet.- Learning Textual Entailment on a Distance Feature Space.- An Inference Model for Semantic Entailment in Natural Language.- A Lexical Alignment Model for Probabilistic Textual Entailment.- Textual Entailment Recognition Using Inversion Transduction Grammars.- Evaluating Semantic Evaluations: How RTE Measures Up.- Partial Predicate Argument Structure Matching for Entailment Determination.- VENSES – A Linguistically-Based System for Semantic Evaluation.- Textual Entailment Recognition Using a Linguistically–Motivated Decision Tree Classifier.- Recognizing Textual Entailment Via Atomic Propositions.- Recognising Textual Entailment with Robust Logical Inference.- Applying COGEX to Recognize Textual Entailment.- Recognizing Textual Entailment: Is Word Similarity Enough?.
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Book by JOAQUIN QUINONEROCANDELA
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Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine . / Lecture Notes in Artificial Intelligence)
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Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine ... (Lecture Notes in Computer Science, 3944)
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Paperback. Condizione: new. Paperback. This book constitutes the thoroughly refereed post-proceedings of the First PASCAL (pattern analysis, statistical modelling and computational learning) Machine Learning Challenges Workshop, MLCW 2005, held in Southampton, UK in April 2005. The 25 revised full papers presented were carefully selected during two rounds of reviewing and improvement from about 50 submissions. The papers reflect the concepts of three challenges dealt with in the workshop: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; the second challenge was to recognize objects from a number of visual object classes in realistic scenes; the third challenge of recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding. Constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783540334279
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Machine Learning Challenges
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding. 484 pp. Englisch. Codice articolo 9783540334279
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Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop
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ISBN 13: 9783540334279
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 484 pp. Englisch. Codice articolo 9783540334279
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Machine Learning Challenges : Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding. Codice articolo 9783540334279
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Machine Learning Challenges | Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
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Taschenbuch. Condizione: Neu. Machine Learning Challenges | Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers | Joaquin Quinonero-Candela (u. a.) | Taschenbuch | xiii | Englisch | 2006 | Springer | EAN 9783540334279 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 102218789
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