This book constitutes the refereed proceedings of the 14th International Conference on Scalable Uncertainty Management, SUM 2020, which was held in Bozen-Bolzano, Italy, in September 2020. The 12 full, 7 short papers presented in this volume were carefully reviewed and selected from 30 submissions.

Symbolic Logic Meets Machine Learning: A Brief Survey in Infinite Domains.- Score-Based Explanations in Data Management and Machine Learning.- From Ppossibilistic Rule-Based 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 Plackett–Luce model: Application to Label Ranking.- Inference with Choice Functions Made Practical.- A Formal Learning Theory for Three-way 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 Decision-Making.- Evidence Theory Based Combination of Frequent Chronicles for Failure Prediction.-Rule-Based Classification for Evidential Data.- Undecided Voters as Set-Valued Information -- Towards Forecasts under Epistemic Imprecision.- Multi-Dimensional 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 Min-Sum Networks.- An Algorithm for the Contension Inconsistency Measure using Reductions to Answer Set Programming.

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