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 /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Quinonero-Candela, Joaquin (Editor ), Dagan, Ido (Editor ), Magnini, Bernardo (Editor ), d'Alché-Buc, Florence (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Colección:Lecture Notes in Artificial Intelligence, 3944
Temas:
Artificial intelligence.
Algorithms.
Machine theory.
Natural language processing (Computer science).
Computer vision.
Pattern recognition systems.
Artificial Intelligence.
Formal Languages and Automata Theory.
Natural Language Processing (NLP).
Computer Vision.
Automated Pattern Recognition.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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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