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Applications in Statistical Computing [[electronic resource] ] : From Music Data Analysis to Industrial Quality Improvement / / edited by Nadja Bauer, Katja Ickstadt, Karsten Lübke, Gero Szepannek, Heike Trautmann, Maurizio Vichi
| Applications in Statistical Computing [[electronic resource] ] : From Music Data Analysis to Industrial Quality Improvement / / edited by Nadja Bauer, Katja Ickstadt, Karsten Lübke, Gero Szepannek, Heike Trautmann, Maurizio Vichi |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 340 p. 83 illus., 48 illus. in color.) |
| Disciplina | 519.5 |
| Collana | Studies in Classification, Data Analysis, and Knowledge Organization |
| Soggetto topico |
Statistics
Data mining Mathematical statistics Mathematics Operations research Decision making Statistics and Computing/Statistics Programs Data Mining and Knowledge Discovery Applied Statistics Probability and Statistics in Computer Science Mathematics in Music Operations Research/Decision Theory |
| ISBN | 3-030-25147-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I Methodological Developments in Data Science.-Aviation Data Analysis by Linear Programming in Airline Network Revenue Management -- Bayesian Reduced Rank Regression for Classification -- Modelling and classification of GC/IMS breath gas measurements for lozenges of different flavours -- The Cosine Depth Distribution Classifier for Directional Data -- A Nonconformity Ratio Based Desirability Function for Capability Assessment -- Part II Computational Statistics -- Heteroscedastic Discriminant Analysis using R -- Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package flacco -- Part III Perspectives on Statistics and Data Science -- A Note on Artificial Intelligence and Statistics -- Statistical Computing and Data Science in Introductory Statistics -- Approaching Ethical Guidelines for Data Scientists -- Part IV Statistics in Econometric Applications -- Dating Lower Turning Points of Business Cycles – a Multivariate Linear Discriminant Analysis for Germany 1984 to 2009 -- Partial Orderings of Default Predictions -- Improving GMM efficiency in dynamic models for panel data with mean stationarity -- Part V Statistics in Industrial Applications -- Economically designed Bayesian np control charts using dual sample sizes for long-run processes -- Statistical analysis of the lifetime of diamond impregnated tools for core drilling of concrete -- Detection of anomalous sequences in crack data of a bridge monitoring -- Optimal Semi-Split-Plot Designs with R -- Continuous process monitoring through ensemble based anomaly detection -- Part VI Statistics in Music Applications -- Evaluation of Audio Feature Groups for the Prediction of Arousal and Valence in Music -- The Psychological Foundations of Classification. |
| Record Nr. | UNINA-9910349330403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Evolutionary Multi-Criterion Optimization [[electronic resource] ] : 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings / / edited by Heike Trautmann, Günter Rudolph, Kathrin Klamroth, Oliver Schütze, Margaret Wiecek, Yaochu Jin, Christian Grimme
| Evolutionary Multi-Criterion Optimization [[electronic resource] ] : 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings / / edited by Heike Trautmann, Günter Rudolph, Kathrin Klamroth, Oliver Schütze, Margaret Wiecek, Yaochu Jin, Christian Grimme |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XIV, 702 p. 267 illus.) |
| Disciplina | 004 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Numerical analysis
Algorithms Computer science Artificial intelligence Computer networks Numerical Analysis Models of Computation Artificial Intelligence Computer Communication Networks |
| ISBN | 3-319-54157-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | On the effect of scalarising norm choice in a ParEGO implementation -- Multi-objective big data optimization with Metal and Spark -- An empirical assessment of the properties of inverted generational distance indicators on multi- and many-objective optimization -- Solving the Bi-objective traveling thief problem with multi-objective evolutionary algorithms -- Automatically Configuring multi-objective local search using multi-objective optimization -- The multi-objective shortest path problem is NP-hard, or is it -- Angle-based preference models in multi-objective optimization -- Quantitative performance assessment of multi-objective optimizers: The average runtime attainment function -- A multi-objective strategy to allocate roadside units in a vehicular network with guaranteed levels of service -- An approach for the local exploration of discrete many objective optimization problems -- A note on the detection of outliers in a binary outranking relation -- Classifying meta-modeling methodologies for evolutionary multi-objective optimization: First results -- Weighted stress function method for multi-objective evolutionary algorithm based on decomposition -- Timing the decision support for real-world many-objective problems -- On the influence of altering the action set on PROMETHEE II's relative ranks -- Peek { Shape { Grab: a methodology in three stages for approximating the non-dominated points of multi-objective discrete combinatorial optimization problems with a multi-objective meta-heuristic -- A new reduced-length genetic representation for evolutionary multi-objective clustering -- A fast incremental BSP tree archive for non-dominated points -- Adaptive operator selection for many-objective optimization with NSGA-III -- On using decision maker preferences with ParEGO -- First investigations on noisy model-based multi-objective optimization -- Fusion of many-objective non-dominated solutions using reference points -- An expedition to multi-modal multi-objective optimization landscapes -- Neutral neighbors in Bi-objective optimization: Distribution of the most promising for permutation problems -- Multi-objective adaptation of a parameterized GVGAI agent towards several games -- Towards standardized and seamless integration of expert knowledge into multi-objective evolutionary optimization algorithms -- Empirical investigations of reference point based methods when facing a massively large number of objectives: First results -- Building and using an ontology of preference-based multi-objective evolutionary algorithms -- A fitness landscape analysis of pareto local search on Bi-objective permutation flow-shop scheduling problems -- Dimensionality reduction approach for many-objective vehicle routing problem with demand responsive transport -- Heterogeneous evolutionary swarms with partial redundancy solving multi-objective tasks -- Multiple meta-models for robustness estimation in multi-objective robust optimization -- Predator-Prey techniques for solving multi-objective scheduling problems for unrelated parallel machines -- An overview of weighted and unconstrained scalarizing functions -- Multi-objective representation setups for deformation-based design optimization -- Design perspectives of an evolutionary process for multi-objective molecular optimization -- Towards a better balance of diversity and convergence in NSGA-III: First results -- A comparative study of fast adaptive preference-guided evolutionary multi-objective optimization -- A population-based algorithm for learning a majority rule sorting model with coalitional veto -- Injection of extreme points in evolutionary multio-objective optimization algorithms -- The impact of population size, number of children, and number of reference points on the performance of NSGA-III -- Multi-objective optimization for liner shipping fleet repositioning -- Surrogate-assisted partial order-based evolutionary optimization -- Hyper-volume indicator gradient ascent multi-objective optimization -- Toward step-size adaptation in evolutionary multi-objective optimization -- Computing 3-D expected hyper-volume improvement and related integrals in asymptotically optimal time. |
| Record Nr. | UNISA-996466082803316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Evolutionary Multi-Criterion Optimization [[electronic resource] ] : 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings / / edited by Heike Trautmann, Günter Rudolph, Kathrin Klamroth, Oliver Schütze, Margaret Wiecek, Yaochu Jin, Christian Grimme
| Evolutionary Multi-Criterion Optimization [[electronic resource] ] : 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings / / edited by Heike Trautmann, Günter Rudolph, Kathrin Klamroth, Oliver Schütze, Margaret Wiecek, Yaochu Jin, Christian Grimme |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XIV, 702 p. 267 illus.) |
| Disciplina | 004 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Numerical analysis
Algorithms Computer science Artificial intelligence Computer networks Numerical Analysis Models of Computation Artificial Intelligence Computer Communication Networks |
| ISBN | 3-319-54157-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | On the effect of scalarising norm choice in a ParEGO implementation -- Multi-objective big data optimization with Metal and Spark -- An empirical assessment of the properties of inverted generational distance indicators on multi- and many-objective optimization -- Solving the Bi-objective traveling thief problem with multi-objective evolutionary algorithms -- Automatically Configuring multi-objective local search using multi-objective optimization -- The multi-objective shortest path problem is NP-hard, or is it -- Angle-based preference models in multi-objective optimization -- Quantitative performance assessment of multi-objective optimizers: The average runtime attainment function -- A multi-objective strategy to allocate roadside units in a vehicular network with guaranteed levels of service -- An approach for the local exploration of discrete many objective optimization problems -- A note on the detection of outliers in a binary outranking relation -- Classifying meta-modeling methodologies for evolutionary multi-objective optimization: First results -- Weighted stress function method for multi-objective evolutionary algorithm based on decomposition -- Timing the decision support for real-world many-objective problems -- On the influence of altering the action set on PROMETHEE II's relative ranks -- Peek { Shape { Grab: a methodology in three stages for approximating the non-dominated points of multi-objective discrete combinatorial optimization problems with a multi-objective meta-heuristic -- A new reduced-length genetic representation for evolutionary multi-objective clustering -- A fast incremental BSP tree archive for non-dominated points -- Adaptive operator selection for many-objective optimization with NSGA-III -- On using decision maker preferences with ParEGO -- First investigations on noisy model-based multi-objective optimization -- Fusion of many-objective non-dominated solutions using reference points -- An expedition to multi-modal multi-objective optimization landscapes -- Neutral neighbors in Bi-objective optimization: Distribution of the most promising for permutation problems -- Multi-objective adaptation of a parameterized GVGAI agent towards several games -- Towards standardized and seamless integration of expert knowledge into multi-objective evolutionary optimization algorithms -- Empirical investigations of reference point based methods when facing a massively large number of objectives: First results -- Building and using an ontology of preference-based multi-objective evolutionary algorithms -- A fitness landscape analysis of pareto local search on Bi-objective permutation flow-shop scheduling problems -- Dimensionality reduction approach for many-objective vehicle routing problem with demand responsive transport -- Heterogeneous evolutionary swarms with partial redundancy solving multi-objective tasks -- Multiple meta-models for robustness estimation in multi-objective robust optimization -- Predator-Prey techniques for solving multi-objective scheduling problems for unrelated parallel machines -- An overview of weighted and unconstrained scalarizing functions -- Multi-objective representation setups for deformation-based design optimization -- Design perspectives of an evolutionary process for multi-objective molecular optimization -- Towards a better balance of diversity and convergence in NSGA-III: First results -- A comparative study of fast adaptive preference-guided evolutionary multi-objective optimization -- A population-based algorithm for learning a majority rule sorting model with coalitional veto -- Injection of extreme points in evolutionary multio-objective optimization algorithms -- The impact of population size, number of children, and number of reference points on the performance of NSGA-III -- Multi-objective optimization for liner shipping fleet repositioning -- Surrogate-assisted partial order-based evolutionary optimization -- Hyper-volume indicator gradient ascent multi-objective optimization -- Toward step-size adaptation in evolutionary multi-objective optimization -- Computing 3-D expected hyper-volume improvement and related integrals in asymptotically optimal time. |
| Record Nr. | UNINA-9910483648603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Parallel Problem Solving from Nature – PPSN XVI [[electronic resource] ] : 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I / / edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann
| Parallel Problem Solving from Nature – PPSN XVI [[electronic resource] ] : 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I / / edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XXIX, 735 p. 261 illus., 169 illus. in color.) |
| Disciplina | 004.0151 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Artificial intelligence Computer science—Mathematics Discrete mathematics Mathematical statistics Computer networks Theory of Computation Artificial Intelligence Mathematics of Computing Discrete Mathematics in Computer Science Probability and Statistics in Computer Science Computer Communication Networks |
| ISBN | 3-030-58112-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automated Algorithm Selection and Configuration -- Bayesian- and Surrogate-Assisted Optimization -- Benchmarking and Performance Measures -- Combinatorial Optimization -- Connection Between Nature-Inspired Optimization and Artificial Intelligence -- Genetic and Evolutionary Algorithms. |
| Record Nr. | UNISA-996418291703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Parallel Problem Solving from Nature – PPSN XVI [[electronic resource] ] : 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II / / edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann
| Parallel Problem Solving from Nature – PPSN XVI [[electronic resource] ] : 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II / / edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XXIX, 717 p. 318 illus., 146 illus. in color.) |
| Disciplina | 004.0151 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Artificial intelligence Computer science—Mathematics Discrete mathematics Software engineering Mathematical statistics Theory of Computation Artificial Intelligence Mathematics of Computing Discrete Mathematics in Computer Science Software Engineering Probability and Statistics in Computer Science |
| ISBN | 3-030-58115-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Genetic Programming -- Landscape Analysis -- Multiobjective Optimization -- Real-World Applications -- Reinforcement Learning -- Theoretical Aspects of Nature-Inspired Optimization. . |
| Record Nr. | UNISA-996418292103316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Parallel Problem Solving from Nature – PPSN XVI [[electronic resource] ] : 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II / / edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann
| Parallel Problem Solving from Nature – PPSN XVI [[electronic resource] ] : 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II / / edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XXIX, 717 p. 318 illus., 146 illus. in color.) |
| Disciplina | 004.0151 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Artificial intelligence Computer science—Mathematics Discrete mathematics Software engineering Mathematical statistics Theory of Computation Artificial Intelligence Mathematics of Computing Discrete Mathematics in Computer Science Software Engineering Probability and Statistics in Computer Science |
| ISBN | 3-030-58115-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Genetic Programming -- Landscape Analysis -- Multiobjective Optimization -- Real-World Applications -- Reinforcement Learning -- Theoretical Aspects of Nature-Inspired Optimization. . |
| Record Nr. | UNINA-9910427719103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Parallel Problem Solving from Nature – PPSN XVI [[electronic resource] ] : 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I / / edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann
| Parallel Problem Solving from Nature – PPSN XVI [[electronic resource] ] : 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I / / edited by Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmann |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XXIX, 735 p. 261 illus., 169 illus. in color.) |
| Disciplina | 004.0151 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Artificial intelligence Computer science—Mathematics Discrete mathematics Mathematical statistics Computer networks Theory of Computation Artificial Intelligence Mathematics of Computing Discrete Mathematics in Computer Science Probability and Statistics in Computer Science Computer Communication Networks |
| ISBN | 3-030-58112-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automated Algorithm Selection and Configuration -- Bayesian- and Surrogate-Assisted Optimization -- Benchmarking and Performance Measures -- Combinatorial Optimization -- Connection Between Nature-Inspired Optimization and Artificial Intelligence -- Genetic and Evolutionary Algorithms. |
| Record Nr. | UNINA-9910427719203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||