> Details
Quiñonero-Candela, Joaquin
[Other];
Dagan, Ido
[Other];
d'Alché-Buc, Florence
[Other];
Magnini, Bernardo
[Other]
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
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- Media type: E-Book; Conference Proceedings
- Title: 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
- Contributor: Quiñonero-Candela, Joaquin [Other]; Dagan, Ido [Other]; d'Alché-Buc, Florence [Other]; Magnini, Bernardo [Other]
- imprint: Berlin, Heidelberg: Springer Berlin Heidelberg, 2006
-
Published in:
Lecture notes in computer science ; 3944
Bücher - Extent: Online-Ressource (XIII, 462 p. Also available online, digital)
- Language: English
- DOI: 10.1007/11736790
- ISBN: 9783540334286
- Identifier:
-
RVK notation:
SS 4800 : Lecture notes in computer science
-
Keywords:
Maschinelles Lernen
>
Statistisches Modell
Maschinelles Lernen > Unsicherheit > Prädiktionsanalyse
Maschinelles Lernen > Bilderkennung > Automatische Klassifikation
Maschinelles Lernen > Automatische Sprachanalyse
Maschinelles Lernen > Dokumentanalyse
Maschinelles Lernen > Statistisches Modell
Maschinelles Lernen > Unsicherheit > Prädiktionsanalyse
Maschinelles Lernen > Bilderkennung > Automatische Klassifikation
Maschinelles Lernen > Automatische Sprachanalyse
Maschinelles Lernen > Dokumentanalyse
- Origination:
-
Footnote:
Literaturangaben
Lizenzpflichtig
- Description: 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?.