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1. |
Record Nr. |
UNINA9910751100403321 |
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Titolo |
Corpus della pittura monumentale bizantina in Italia : 1. Umbria / a cura di Mara Bonfioli |
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Pubbl/distr/stampa |
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Roma, : Edizioni Quasar, 2012 |
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ISBN |
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Descrizione fisica |
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Locazione |
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Collocazione |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Testi di: Mara Bonfioli, Livia Bevilacqua, Mauro della Valle, Simona Moretti, Cristina Pantalla. |
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2. |
Record Nr. |
UNINA9910682588503321 |
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Titolo |
Evolutionary Multi-Criterion Optimization : 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20–24, 2023, Proceedings / / edited by Michael Emmerich, André Deutz, Hao Wang, Anna V. Kononova, Boris Naujoks, Ke Li, Kaisa Miettinen, Iryna Yevseyeva |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (646 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 13970 |
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Disciplina |
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Soggetti |
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Algorithms |
Computer science - Mathematics |
Artificial intelligence |
Computers |
Computer networks |
Social sciences - Data processing |
Design and Analysis of Algorithms |
Mathematics of Computing |
Artificial Intelligence |
Computing Milieux |
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Computer Communication Networks |
Computer Application in Social and Behavioral Sciences |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Algorithm Design and Engineering -- Visual Exploration of the Effect of Constraint Handling in Multiobjective Optimization -- A Two-stage Algorithm for Integer Multiobjective Simulation Optimization -- RegEMO: Sacrificing Pareto-Optimality for Regularity in Multi-objective Problem-Solving -- Cooperative coevolutionary NSGA-II with Linkage Measurement Minimization for Large-scale Multi-objective Optimization -- Data-Driven Evolutionary Multi-Objective Optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts -- Eliminating Non-dominated Sorting from NSGA-III -- Scalability of Multi-Objective Evolutionary Algorithms for Solving Real-World Complex Optimization Problems -- Machine Learning and Multi-criterion Optimization -- Multi-Objective Learning using HV Maximization -- Sparse Adversarial Attack via Bi-Objective Optimization -- Investigating Innovized Progress Operators with Different Machine Learning Methods -- End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location -- Online Learning Hyper-Heuristics in Multi-Objective Evolutionary Algorithms -- Surrogate-assisted Multi-objective Optimization via Genetic Programming based Symbolic Regression -- Learning to Predict Pareto-optimal Solutions From Pseudo-weights -- A Relation Surrogate Model for Expensive Multiobjective Continuous and Combinatorial Optimization -- Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling -- Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling -- Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables -- Feature-based Benchmarking of Distance-based Multi/Many-objective Optimisation Problems: A Machine Learning Perspective -- Benchmarking and Performance Assessment -- Partially Degenerate Multi-Objective Test Problems -- Peak-A-Boo! GeneratingMulti-Objective Multiple Peaks Benchmark Problems with Precise Pareto Sets -- MACO: A Real-world inspired Benchmark for Multi-objective Evolutionary Algorithms -- A scalable test suite for bi-objective multidisciplinary optimisation -- Performance Evaluation of Multi-Objective Evolutionary Algorithms using Artificial and Real-World Problems -- A Novel Performance Indicator based on the Linear Assignment Problem -- A Test Suite for Multi-objective Multi-fidelity Optimization -- Indicator Design and Complexity Analysis -- Diversity enhancement via magnitude -- Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems -- Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems -- On the Computational Complexity of Efficient Non-Dominated Sort using Binary Search -- Applications in Real World Domains -- Evolutionary Algorithms with Machine Learning Models for Multiobjective Optimization in Epidemics Control -- Joint Price Optimization across a Portfolio of Fashion E-commerce Products -- Improving MOEA/D with Knowledge Discovery. Application to a Bi- |
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Objective Routing Problem -- The Prism-Net Search Space Representation for Multi-Objective Building Spatial Design -- Selection Strategies for a Balanced Multi- or Many-Objective Molecular Optimization and Genetic Diversity: a Comparative Study -- A Multi-objective Evolutionary Framework for Identifying Dengue Stage-Specific Differentially Co-expressed and Functionally Enriched Gene Modules -- A Multi-objective Evolutionary Framework for Identifying Dengue Stage-Specific Differentially Co-expressed and Functionally Enriched Gene Modules. -Multiobjective Optimization of Evolutionary Neural Networks for Animal Trade Movements Prediction -- Transfer of Multi-Objectively Tuned CMA-ES Parameters to a Vehicle Dynamics Problem -- Multi-Criteria Decision Making and Interactive Algorithms -- Preference-Based Nonlinear Normalization for Multiobjective Optimization -- Incorporating preference information interactively in NSGA-III by the adaptation of reference vectors -- A Systematic Way of Structuring Real-World Multiobjective Optimization Problems -- IK-EMOViz: An Interactive Knowledge-based Evolutionary Multi-objective Optimization Framework -- An Interactive Decision Tree-Based Evolutionary Multi-Objective Algorithm. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the 12th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2022 held in Leiden, The Netherlands, during March 20-24, 2023. The 44 regular papers presented in this book were carefully reviewed and selected from 65 submissions. The papers are divided into the following topical sections: Algorithm Design and Engineering; Machine Learning and Multi-criterion Optimization; Benchmarking and Performance Assessment; Indicator Design and Complexity Analysis; Applications in Real World Domains; and Multi-Criteria Decision Making and Interactive Algorithms. |
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