Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science
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9783540334279, 9783540334286

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Evaluating Semantic Evaluations: How RTE Measures Up

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_18 ◽

2006 ◽

pp. 309-331 ◽

Cited By ~ 1

Author(s):

Sam Bayer ◽

John Burger ◽

Lisa Ferro ◽

John Henderson ◽

Lynette Hirschman ◽

...

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VENSES – A Linguistically-Based System for Semantic Evaluation

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_20 ◽

2006 ◽

pp. 344-371 ◽

Cited By ~ 3

Author(s):

Rodolfo Delmonte ◽

Sara Tonelli ◽

Marco Aldo Piccolino Boniforti ◽

Antonella Bristot

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Estimating Predictive Variances with Kernel Ridge Regression

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_5 ◽

2006 ◽

pp. 56-77 ◽

Cited By ~ 6

Author(s):

Gavin C. Cawley ◽

Nicola L. C. Talbot ◽

Olivier Chapelle

Keyword(s):

Ridge Regression ◽

Kernel Ridge Regression

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Applying COGEX to Recognize Textual Entailment

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_24 ◽

2006 ◽

pp. 427-448 ◽

Cited By ~ 2

Author(s):

Daniel Hodges ◽

Christine Clark ◽

Abraham Fowler ◽

Dan Moldovan

Keyword(s):

Textual Entailment

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What Syntax Can Contribute in the Entailment Task

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_11 ◽

2006 ◽

pp. 205-216 ◽

Cited By ~ 10

Author(s):

Lucy Vanderwende ◽

William B. Dolan

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Many Are Better Than One: Improving Probabilistic Estimates from Decision Trees

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_4 ◽

2006 ◽

pp. 41-55 ◽

Cited By ~ 6

Author(s):

Nitesh V. Chawla

Keyword(s):

Decision Trees ◽

Better Than

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Textual Entailment Recognition Using a Linguistically–Motivated Decision Tree Classifier

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_21 ◽

2006 ◽

pp. 372-384

Author(s):

Eamonn Newman ◽

Nicola Stokes ◽

John Dunnion ◽

Joe Carthy

Keyword(s):

Decision Tree ◽

Decision Tree Classifier ◽

Tree Classifier ◽

Textual Entailment

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Evaluating Predictive Uncertainty Challenge

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_1 ◽

2006 ◽

pp. 1-27 ◽

Cited By ~ 20

Author(s):

Joaquin Quiñonero-Candela ◽

Carl Edward Rasmussen ◽

Fabian Sinz ◽

Olivier Bousquet ◽

Bernhard Schölkopf

Keyword(s):

Predictive Uncertainty

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A Pragmatic Bayesian Approach to Predictive Uncertainty

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_3 ◽

2006 ◽

pp. 33-40

Author(s):

Iain Murray ◽

Edward Snelson

Keyword(s):

Bayesian Approach ◽

Predictive Uncertainty

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Classification with Bayesian Neural Networks

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science ◽

10.1007/11736790_2 ◽

2006 ◽

pp. 28-32

Author(s):

Radford M. Neal

Keyword(s):

Neural Networks ◽

Bayesian Neural Networks

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Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Evaluating Semantic Evaluations: How RTE Measures Up

VENSES – A Linguistically-Based System for Semantic Evaluation

Estimating Predictive Variances with Kernel Ridge Regression

Applying COGEX to Recognize Textual Entailment

What Syntax Can Contribute in the Entailment Task

Many Are Better Than One: Improving Probabilistic Estimates from Decision Trees

Textual Entailment Recognition Using a Linguistically–Motivated Decision Tree Classifier

Evaluating Predictive Uncertainty Challenge

A Pragmatic Bayesian Approach to Predictive Uncertainty

Classification with Bayesian Neural Networks

Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment - Lecture Notes in Computer Science
Latest Publications