Scalable Uncertainty Management 13th International Conference, SUM 2019, Compiègne, France, December 16-18, 2019, Proceedings /

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 se...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Ben Amor, Nahla (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Quost, Benjamin (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Theobald, Martin (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Lecture Notes in Artificial Intelligence ; 11940
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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 Forgetting Explaining 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 measure of 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.