TY  - BOOK
AU  - 
AU  - 
AU  - 
AU  - 
ED  - SpringerLink (Online service)
TI  - 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 
T2  - Lecture Notes in Computer Science,
SN  - 9783540334286
AV  - Q334-342 
U1  - 006.3 23
PY  - 2006///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Computer software
KW  - Artificial intelligence
KW  - Text processing (Computer science
KW  - Computer vision
KW  - Optical pattern recognition
KW  - Computer Science
KW  - Artificial Intelligence (incl. Robotics)
KW  - Algorithm Analysis and Problem Complexity
KW  - Mathematical Logic and Formal Languages
KW  - Document Preparation and Text Processing
KW  - Image Processing and Computer Vision
KW  - Pattern Recognition
N1  - 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 LinguisticallyMotivated 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?; ZDB-2-SCS; ZDB-2-LNC
UR  - http://dx.doi.org/10.1007/11736790
ER  -