Lecture Notes in Computer Science - Scalable Uncertainty Management
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Published By Springer International Publishing

9783030584481, 9783030584498

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A Formal Learning Theory for Three-Way Clustering

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_9 ◽

2020 ◽

pp. 128-140

Author(s):

Andrea Campagner ◽

Davide Ciucci

Keyword(s):

Learning Theory ◽

Formal Learning ◽

Formal Learning Theory

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From Possibilistic Rule-Based Systems to Machine Learning - A Discussion Paper

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_3 ◽

2020 ◽

pp. 35-51

Author(s):

Didier Dubois ◽

Henri Prade

Keyword(s):

Machine Learning ◽

Discussion Paper ◽

Rule Based ◽

Rule Based Systems

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Symbolic Logic Meets Machine Learning: A Brief Survey in Infinite Domains

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_1 ◽

2020 ◽

pp. 3-16

Author(s):

Vaishak Belle

Keyword(s):

Machine Learning ◽

Symbolic Logic ◽

Infinite Domains

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Inference with Choice Functions Made Practical

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_8 ◽

2020 ◽

pp. 113-127

Author(s):

Arne Decadt ◽

Jasper De Bock ◽

Gert de Cooman

Keyword(s):

Choice Functions

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An Algorithm for the Contension Inconsistency Measure Using Reductions to Answer Set Programming

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_23 ◽

2020 ◽

pp. 289-296

Author(s):

Isabelle Kuhlmann ◽

Matthias Thimm

Keyword(s):

Answer Set Programming ◽

Answer Set

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Evidence Theory Based Combination of Frequent Chronicles for Failure Prediction

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_16 ◽

2020 ◽

pp. 226-233

Author(s):

Achraf Ben Chrayet ◽

Ahmed Samet ◽

Mohamed Anis Bach Tobji

Keyword(s):

Evidence Theory ◽

Failure Prediction

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Conversational Recommender System by Bayesian Methods

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_14 ◽

2020 ◽

pp. 200-214

Author(s):

Francesca Mangili ◽

Denis Broggini ◽

Alessandro Antonucci

Keyword(s):

Bayesian Methods ◽

Recommender System

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Score-Based Explanations in Data Management and Machine Learning

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_2 ◽

2020 ◽

pp. 17-31

Author(s):

Leopoldo Bertossi

Keyword(s):

Machine Learning ◽

Data Management

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Belief Functions for Safety Arguments Confidence Estimation: A Comparative Study

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_10 ◽

2020 ◽

pp. 141-155

Author(s):

Yassir Idmessaoud ◽

Didier Dubois ◽

Jérémie Guiochet

Keyword(s):

Comparative Study ◽

Belief Functions ◽

Confidence Estimation

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Measuring Disagreement with Interpolants

Lecture Notes in Computer Science - Scalable Uncertainty Management ◽

10.1007/978-3-030-58449-8_6 ◽

2020 ◽

pp. 84-97

Author(s):

Jandson S. Ribeiro ◽

Viorica Sofronie-Stokkermans ◽

Matthias Thimm

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Lecture Notes in Computer Science - Scalable Uncertainty ManagementLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

A Formal Learning Theory for Three-Way Clustering

From Possibilistic Rule-Based Systems to Machine Learning - A Discussion Paper

Symbolic Logic Meets Machine Learning: A Brief Survey in Infinite Domains

Inference with Choice Functions Made Practical

An Algorithm for the Contension Inconsistency Measure Using Reductions to Answer Set Programming

Evidence Theory Based Combination of Frequent Chronicles for Failure Prediction

Conversational Recommender System by Bayesian Methods

Score-Based Explanations in Data Management and Machine Learning

Belief Functions for Safety Arguments Confidence Estimation: A Comparative Study

Measuring Disagreement with Interpolants

Lecture Notes in Computer Science - Scalable Uncertainty Management
Latest Publications