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[null,null,"Titolo",null,"Machine Learning Challenges [[electronic resource] ] : 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 / / edited by Joaquin Quinonero-Candela, Ido Dagan, Bernardo Magnini, Florence d'Alché-Buc"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006"]
[null,null,"ISBN",null,"3-540-33428-9"]
[null,null,"Edizione",null,"[1st ed. 2006.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XIII, 462 p.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence ; ; 3944"]
[null,null,"Disciplina",null,"006.3/1"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Mathematical logic"]
[{"$nulls":4},"Natural language processing (Computer science)"]
[{"$nulls":4},"Optical data processing"]
[{"$nulls":4},"Pattern recognition"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Algorithm Analysis and Problem Complexity"]
[{"$nulls":4},"Mathematical Logic and Formal Languages"]
[{"$nulls":4},"Natural Language Processing (NLP)"]
[{"$nulls":4},"Image Processing and Computer Vision"]
[{"$nulls":4},"Pattern Recognition"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Evaluating Predictive Uncertainty Challenge -- Classification with Bayesian Neural Networks -- A Pragmatic Bayesian Approach to Predictive Uncertainty -- Many Are Better Than One: Improving Probabilistic Estimates from Decision Trees -- Estimating Predictive Variances with Kernel Ridge Regression -- Competitive Associative Nets and Cross-Validation for Estimating Predictive Uncertainty on Regression Problems -- Lessons Learned in the Challenge: Making Predictions and Scoring Them -- The 2005 PASCAL Visual Object Classes Challenge -- The PASCAL Recognising Textual Entailment "]
[{"$nulls":4},"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?."]