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duxiu/initial_release/Lecture Notes in Artificial Intelligence 3944 Machine Learning Challenges Evaluating Predictive Uncertainty Visual Object Classification and Recognizing Texyual Entailment_40368808.zip
Lecture Notes in Artificial Intelligence 3944 Machine Learning Challenges Evaluating Predictive Uncertainty Visual Object Classification and Recognizing Texyual Entailment 🔍
Florence D'Alché-Buc, Ido Dagan, Bernardo Magnini, Joaquin Quiñonero-Candela, MLCW 2005, Machine Learning Challenges Workshop, PASCAL Machine Learning Challenges Workshop, Joaquin Quiñonero-Candela, PASCAL Machine Learning Challenges Workshop, MLCW Springer Spektrum. in Springer-Verlag GmbH, Lecture notes in computer science, 3944, 1st ed. 2006, Berlin, Heidelberg, 2006
英语 [en] · PDF · 243.9MB · 2006 · 📗 未知类型的图书 · 🚀/duxiu/zlibzh · Save
描述
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.
备用文件名
zlibzh/no-category/Florence D'Alché-Buc, Ido Dagan, Bernardo Magnini, Joaquin Quiñonero-Candela, MLCW 2005, Machine Learning Challenges Workshop, PASCAL Machine Learning Challenges Workshop, Joaquin Quiñonero-Candela, PASCAL Machine Learning Challenges Workshop, MLCW/Lecture Notes in Artificial Intelligence 3944 Machine Learning Challenges Evaluating Predictive Uncertainty Visual Object Classification and Recognizing Texyual Entailment_117078858.pdf
备选标题
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
备选标题
Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment : First PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
备选标题
Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine ... Papers (Lecture Notes in Computer Science)
备选标题
Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine ... (Lecture Notes in Computer Science, 3944)
备选标题
Machine learning challenges evaluating predictive uncertainty, visual object classification, and recognising textual entailment ; revised selected papers
备选作者
Joaquin Quinonero-Candela; Ido Dagan; Bernardo Magnini; Florence d'Alché-Buc; PASCAL Machine Learning Challenges Workshop
备选作者
PASCAL Machine Learning Challenges Workshop (1st 2005 Southampton, England)
备选作者
Joaquin Quiñonero-Candela ... [et al.] (eds.)
备用出版商
Springer Berlin Heidelberg : Imprint: Springer
备用出版商
Steinkopff. in Springer-Verlag GmbH
备用出版商
Springer London, Limited
备用版本
Lecture notes in artificial intelligence -- 3944. -- Lecture notes in artificial intelligence, Lecture notes in computer science -- 3944., Lecture notes in computer science, Berlin, New York, Germany, 2006
备用版本
Lecture notes in computer science, Vol. 3944 : Lecture notes in artificial intelligence, Berlin, 2006
备用版本
Springer Nature, Berlin, 2006
备用版本
1 edition, July 6, 2006
备用版本
Germany, Germany
元数据中的注释
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filepath:/读秀/读秀4.0/读秀/4.0/数据库42-3/Lecture Notes in Artificial Intelligence 3944 Machine Learning Challenges Evaluating Predictive Uncertainty Visual Object Classification and Recognizing Texyual Entailment_40368808.zip
元数据中的注释
Includes bibliographical references and index.
备用描述
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
备用描述
Keine Beschreibung vorhanden.
Erscheinungsdatum: 11.05.2006
开源日期
2024-06-13
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