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1. |
Record Nr. |
UNINA9910335359103321 |
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Autore |
Herrmann, Luke |
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Titolo |
Ruskin and Turner : a study of Ruskin as a collector of Turner, based on his gifts to the University of Oxford, incorporating a Catalogue raisonné of the Turner drawings in the Ashmolean Museum / Luke Herrmann |
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London : Faber & Faber, 1968 |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910153348903321 |
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Autore |
Cyril Bourdois |
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Titolo |
ART DE LA MORT ET MORT DE L'ART - Portraits de groupes, images du sacré, de la mort, de femmes et de diverses choses |
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Pubbl/distr/stampa |
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Paris |
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Editions L'Harmattan |
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2013 |
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ISBN |
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2-336-66991-9 |
2-296-54023-6 |
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Descrizione fisica |
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1 online resource (258 p.) |
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Soggetti |
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Death in art - Philosophy |
Human figure in art |
Art |
Visual Arts |
Art, Architecture & Applied Arts |
Visual Arts - General |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Sommario/riassunto |
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Face à la banalisation des images qui abreuvent notre société, cet ouvrage prend le temps de s'appesantir sur un certain nombre d'entre elles, le lien qui les unit est leur rapport à la mort. Ce parcours propose une réflexion quant au sens des images et à leur place sous le label "art", sans classement préférentiel ni chronologique, privilégiant une approche sensible, la réception de l'art contemporain est ainsi interrogée en relation avec le corpus "patrimonial". |
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3. |
Record Nr. |
UNINA9910357841303321 |
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Titolo |
Scalable Uncertainty Management : 13th International Conference, SUM 2019, Compiègne, France, December 16–18, 2019, Proceedings / / edited by Nahla Ben Amor, Benjamin Quost, Martin Theobald |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (XI, 452 p. 220 illus., 57 illus. in color.) |
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Collana |
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Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 11940 |
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Disciplina |
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Artificial intelligence |
Computer science |
Computer science - Mathematics |
Mathematical statistics |
Artificial Intelligence |
Computer Science Logic and Foundations of Programming |
Probability and Statistics in Computer Science |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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An Experimental Study on the Behaviour of Inconsistency Measures -- Inconsistency Measurement Using Graph Convolutional Networks for |
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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 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. |
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Sommario/riassunto |
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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. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models. |
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