Scalable Uncertainty Management

13th International Conference, SUM 2019, Compiègne, France, December 16–18, 2019, Proceedings

Häftad, Engelska, 2019

Av Nahla Ben Amor, Benjamin Quost, Martin Theobald

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This book constitutes the refereed proceedings of the 13th International Conference on Scalable Uncertainty Management, SUM 2019, which was held in Compiègne, France, in December 2019. The 25 full, 4 short, 4 tutorial, 2 invited keynote papers presented in this volume were carefully reviewed and selected from 44 submissions.

Produktinformation

Utgivningsdatum2019-11-21
Mått155 x 235 x 25 mm
Vikt698 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor452
FörlagSpringer Nature Switzerland AG
ISBN9783030355135

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Matematisk statistik inom Naturvetenskap och teknik
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An Experimental Study on the Behaviour of Inconsistency Measures.- Inconsistency Measurement Using Graph Convolutional Networks for Approximate Reasoning with Abstract Argumentation Frameworks: A Feasibility Study.- The Hidden Elegance of Causal Interaction Models.- Computational Models for Cumulative Prospect Theory: Application to the Knapsack Problem Under Risk.- On a new evidential C-Means algorithm with instance-level constraints.- Hybrid Reasoning on a Bipolar Argumentation Framework.- Active Preference Elicitation by Bayesian Updating on Optimality Polyhedra.- Selecting Relevant Association Rules From Imperfect Data.- Evidential classification of incomplete data via imprecise relabelling: Application to plastic sorting.- An analogical interpolation method for enlarging a training dataset.- Towards a reconciliation between reasoning and learning - A position paper.- CP-nets, π-pref nets, and Pareto dominance.- Measuring Inconsistency through Subformula ForgettingExplaining Hierarchical Multi-Linear Models.- Assertional Removed Sets Merging of DL-Lite Knowledge Bases.- An Interactive Polyhedral Approach for Multi-Objective Combinatorial Optimization with Incomplete Preference Information.- Open-Mindedness of Gradual Argumentation Semantics.- Approximate Querying on Property Graphs.- Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants.- On cautiousness and expressiveness in interval-valued logic.- Preference Elicitation with Uncertainty: Extending Regret Based Methods with Belief Functions.- Evidence Propagation and Consensus Formation in Noisy Environments.- Order-Independent Structure Learning of Multivariate Regression Chain Graphs.- l Comparison of analogy-based methods for predicting preferences.- Using Convolutional Neural Network in Cross-Domain Argumentation Mining Framework.- ConvNet and Dempster-Shafer Theory for Object Recognition.- On learning evidential contextual corrections from soft labels using a measureof discrepancy between contour functions.- Efficient Mo ̈bius Transformations and their applications to D-S Theory.- From shallow to deep interactions between knowledge representation, reasoning and machine learning.- Dealing with Continuous Variables in Graphical Models.- Towards Scalable and Robust Sum-Product Networks.- Learning Models over Relational Data:A Brief Tutorial.- Subspace Clustering and Some Soft Variants.- Algebraic Approximations for Weighted Model Counting.