Description 
1 online resource 
Series 
LNCS sublibrary, SL 7, Artificial intelligence 

Lecture notes in artificial intelligence 

Lecture notes in computer science ; 12322 

LNCS sublibrary. SL 7, Artificial intelligence


Lecture notes in computer science ; 12322


Lecture notes in computer science. Lecture notes in artificial intelligence.

Contents 
Symbolic Logic Meets Machine Learning: A Brief Survey in Infinite Domains. ScoreBased Explanations in Data Management and Machine Learning. From Ppossibilistic RuleBased Systems to Machine Learning. Logic, Probability and Action: A Situation Calculus Perspective. When Nominal Analogical Proportions do not Fail. Measuring Disagreement with Interpolants. Inferring from an imprecise PlackettLuce model: Application to Label Ranking. Inference with Choice Functions Made Practical. A Formal Learning Theory for Threeway Clustering. Belief Functions for Safety Arguments Confidence Estimation. Incremental Elicitation of Capacities for the Sugeno Integral with a Maximum Approach. Computable Randomness is About More than Probabilities. Equity in Learning Problems: an OWA Approach. Conversational Recommender System by Bayesian Methods. Dealing with Atypical Instances in Evidential DecisionMaking. Evidence Theory Based Combination of Frequent Chronicles for Failure Prediction. RuleBased Classification for Evidential Data. Undecided Voters as SetValued Information  Towards Forecasts under Epistemic Imprecision. MultiDimensional Stable Matching Problems in Abstract Argumentation. Modal Interpretation of Formal Concept Analysis for Incomplete Representations. A Symbolic Approach for Counterfactual Explanations. Modelling Multivariate Ranking Functions with MinSum Networks. An Algorithm for the Contension Inconsistency Measure using Reductions to Answer Set Programming 
Summary 
This book constitutes the refereed proceedings of the 14th International Conference on Scalable Uncertainty Management, SUM 2020, which was held in BozenBolzano, Italy, in September 2020. The 12 full, 7 short papers presented in this volume were carefully reviewed and selected from 30 submissions. Besides that, the book also contains 2 abstracts of invited talks, 2 tutorial papers, and 2 PhD track papers. The conference aims to gather researchers with a common interest in managing and analyzing imperfect information from a wide range of fields, such as artificial intelligence and machine learning, databases, information retrieval and data mining, the semantic web and risk analysis. Due to the Corona pandemic SUM 2020 was held as an virtual event 
Notes 
"Unfortunately, the COVID19 pandemic forced the postponement of this event. Therefore, SUM 2020 was changed to a fully virtual conference." Preface 

Includes author index 

International conference proceedings 

Online resource; title from PDF title page (SpringerLink, viewed November 5, 2020) 
Subject 
Uncertainty (Information theory)  Congresses.


Artificial intelligence.


Artificial intelligence.


Computer architecture.


Computer networks.


Computer science  Mathematics.


Computers  Data Processing.


Computers  Database Management  Data Mining.


Computers  Hardware  Network Hardware.


Computers  Information Technology.


Computers  Intelligence (AI) & Semantics.


Data mining.


Data mining.


Machine learning.


Machine learning.


Mathematical theory of computation.


Network hardware.


Systems analysis & design.


Uncertainty (Information theory)

Genre/Form 
Electronic books.


Conference papers and proceedings.

Form 
Electronic book

Author 
Davis, Jesse (Professor of Informatics)


Tabia, Karim.

ISBN 
3030584496 

9783030584498 
