Fuzzy dynamic equations, dynamic inclusions, and optimal control problems on time scales / / Svetlin G. Georgiev |
Autore | Georgiev Svetlin |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (882 pages) |
Disciplina | 531.11 |
Soggetto topico |
Dinàmica
Sistemes borrosos Optimització matemàtica |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-76132-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910492146703321 |
Georgiev Svetlin
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Cham, Switzerland : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Fuzzy dynamic equations, dynamic inclusions, and optimal control problems on time scales / / Svetlin G. Georgiev |
Autore | Georgiev Svetlin |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (882 pages) |
Disciplina | 531.11 |
Soggetto topico |
Dinàmica
Sistemes borrosos Optimització matemàtica |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-76132-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996466397203316 |
Georgiev Svetlin
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Cham, Switzerland : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. di Salerno | ||
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Fuzzy logic hybrid extensions of neural and optimization algorithms : theory and applications / / editors, Oscar Castillo, Patricia Melin |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (ix, 383 pages) : illustrations |
Disciplina | 511.3 |
Collana | Studies in computational intelligence |
Soggetto topico |
Fuzzy logic
Neural networks (Computer science) Soft computing Lògica difusa Xarxes neuronals (Informàtica) Optimització matemàtica Informàtica tova Algorismes |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-68776-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Contents -- Estimation of the Number of Filters in the Convolution Layers of a Convolutional Neural Network Using a Fuzzy Logic System -- 1 Introduction -- 2 Literature Review -- 2.1 Convolutional Neural Networks -- 2.2 GSA -- 2.3 FGSA -- 3 Proposed Method -- 4 Results and Discussion -- 5 Conclusions -- References -- Optimization of Membership Function Parameters for Fuzzy Controllers in Cruise Control Problem Using the Multi-verse Optimizer -- 1 Introduction -- 2 Fuzzy Systems -- 2.1 Mamdani Model -- 2.2 Sugeno Model -- 3 Control Systems -- 4 Metaheuristics and Multi-verse Optimizer -- 4.1 Multi-verse Optimizer -- 4.2 Applications of MVO -- 5 Test and Results -- 5.1 Benchmark Function Test and Results -- 5.2 Applications Test and Results -- 6 Conclusions -- References -- Performance Analysis of a Distributed Steady-State Genetic Algorithm Using Low-Power Computers -- 1 Introduction -- 2 Distributed Steady-State Genetic Algorithm -- 2.1 Application of Distributed Steady-State Genetic Algorithm in the n-Queens Problem -- 2.2 Application of Distributed Steady-State Genetic Algorithm in the Travelling Salesman Problem -- 3 Master-Slave Low Power Architecture -- 3.1 Rationale on Master-Slave Architecture Starting Procedure -- 3.2 Function Evaluation Task on Slave-Devices -- 3.3 Fail-Safe Algorithm on Master-Device -- 4 Computational Results -- 4.1 Experimental Setup -- 4.2 n-Queens Problem Experimental Arrangement Results -- 4.3 Travelling Salesman Problem Results -- 5 Conclusions and Future Work -- References -- Ensemble Recurrent Neural Networks for Complex Time Series Prediction with Integration Methods -- 1 Introduction -- 2 Problem Statement and Proposed Method -- 2.1 Analyze the Time Series -- 2.2 Creation of the Recurrent Neural Network -- 2.3 Integration by Average -- 2.4 Integration by Weighted Average.
2.5 Integration by Gating Network -- 2.6 Type-1 and Type-2 Fuzzy System Integration -- 2.7 Generalized Type-2 Fuzzy System -- 3 Simulation Results -- 4 Conclusions -- References -- Genetic Optimization of Ensemble Neural Network Architectures for Prediction of COVID-19 Confirmed and Death Cases -- 1 Introduction -- 2 Basic Concepts -- 2.1 Artificial Neural Networks -- 2.2 Nonlinear Autoregressive Neural Network -- 2.3 Fuzzy Logic -- 2.4 Genetic Algorithms -- 3 Proposed Method -- 4 Results of the Experiment -- 4.1 Genetic Algorithms -- 5 Conclusions -- References -- Optimization of Modular Neural Networks for the Diagnosis of Cardiovascular Risk -- 1 Introduction -- 2 Literature Review -- 2.1 Flower Pollination Algorithm -- 2.2 Bird Swarm Algorithm -- 2.3 Blood Pressure and Hypertension -- 2.4 Cardiovascular Disease and Heart Age -- 2.5 Framingham Heart Study -- 3 Proposed Method -- 4 Results -- 5 Conclusions and Future Work -- References -- A Review on the Cuckoo Search Algorithm -- 1 Introduction -- 2 An Analogy with Nature -- 2.1 Cuckoo Search Algorithm -- 2.2 Algorithm Rules -- 2.3 Levy Flights -- 2.4 Mathematical Formulas -- 2.5 Flowchart CS -- 3 Implementation of Levy Flights in Other Algorithms -- 4 Variants of the Cuckoo Search Algorithm -- 5 Applications -- 6 Conclusions -- References -- An Improved Convolutional Neural Network Based on a Parameter Modification of the Convolution Layer -- 1 Introduction -- 2 Background and Basic Concepts -- 2.1 Convolutional Neural Network Concepts -- 2.2 Edge Detectors -- 2.3 Sobel Operator -- 2.4 Prewitt Operator -- 2.5 Laplacian Operator -- 3 Proposed Approach -- 3.1 Proposed Architecture -- 3.2 Convolution Kernel Initialization -- 4 Experiments -- 4.1 Case Study MNIST Handwritten Digits -- 4.2 Case Study MNIST American Sign Language -- 4.3 Case Study Mexican Sign Language Database -- 5 Conclusions. References -- Parameter Optimization of a Convolutional Neural Network Using Particle Swarm Optimization -- 1 Introduction -- 2 Convolutional Neural Network -- 2.1 Input Layer -- 2.2 Convolution Layer -- 2.3 Non-linearity Layer -- 2.4 Pooling Layer -- 2.5 Classifier Layer -- 3 Particle Swarm Optimization -- 3.1 Global Best PSO -- 3.2 Local Best PSO -- 4 Proposed Method -- 4.1 Parameter Optimization of the CNN -- 4.2 CNN-PSO Optimization Process -- 5 Experiments and Results -- 5.1 Exploratory Experiment -- 5.2 American Sign Language Alphabet (ASL Alphabet) Experiment -- 5.3 American Sign Language MNIST Experiment -- 5.4 Analysis and Comparison of Results -- 6 Conclusion and Future Work -- References -- One-Dimensional Bin Packing Problem: An Experimental Study of Instances Difficulty and Algorithms Performance -- 1 Introduction -- 2 The Bin Packing Problem -- 2.1 Instances -- 2.2 Index Description -- 2.3 Performance Measures -- 3 Algorithms -- 3.1 First Fit Decreasing (FFD) -- 3.2 Best Fit Decreasing (BFD) -- 3.3 Minimum Bin Slack (MBS) -- 3.4 GGA-CGT -- 4 Results -- 5 Experimental Analysis -- 5.1 Class BPP.25 -- 5.2 Class BPP.5 -- 5.3 Class BPP.75 -- 5.4 Class BPP1 -- 6 Conclusions and Future Work -- References -- Looking for Emotions in Evolutionary Art -- 1 Introduction -- 2 In Search of Lost Emotions -- 2.1 Humans in the EA Loop -- 3 Methodology: Analysis of Emotions in the Era of Evolutionary Art -- 3.1 The Line -- 3.2 Simplifying the Problem -- 3.3 Evospace-Interactive Module -- 4 Results -- 4.1 Analyzing Formal Elements -- 4.2 Are Emotions Properly Understood? -- 4.3 Audience Analysis -- 4.4 International Art Competitions -- 5 Conclusion -- References -- Review of Hybrid Combinations of Metaheuristics for Problem Solving Optimization -- 1 Introduction -- 2 Review of Hybrid or Combined Metaheuristics -- 3 Discussion -- 4 Conclusions. References -- GPU Accelerated Membrane Evolutionary Artificial Potential Field for Mobile Robot Path Planning -- 1 Introduction -- 2 Fundamentals -- 2.1 Membrane Computing -- 2.2 Evolutionary Computation -- 2.3 Artificial Potential Field Method -- 3 GPU Accelerated MemEAPF -- 4 Results -- 4.1 Path Planning Results -- 4.2 Performance Results -- 5 Conclusions -- References -- Optimization of the Internet Shopping Problem with Shipping Costs -- 1 Introduction -- 1.1 Definition of the Problem -- 2 The General Structure of the Memetic Algorithm -- 2.1 Selection by Tournament -- 2.2 Crossover Operator -- 2.3 Mutation Operator -- 2.4 Local Search -- 2.5 Memetic Algorithm (MAIShOP) -- 3 Computational Experiments -- 4 Conclusions -- References -- Multiobjective Algorithms Performance When Solving CEC09 Test Instances -- 1 Introduction -- 2 Multiobjective Optimization -- 3 CEC09 Test Functions -- 4 Multiobjective Optimization Algorithms -- 5 Performance Metrics of Multiobjective Optimization -- 6 Computational Experiments -- 7 Conclusion and Future Work -- References -- Analysis of the Efficient Frontier of the Portfolio Selection Problem Instance of the Mexican Capital Market -- 1 Introduction -- 2 Multiobjective Algorithms in Comparison -- 3 CellDE -- 4 GDE3 -- 5 IBEA -- 6 MOCell -- 7 NSGA-II -- 8 NSGA-III -- 9 OMOPSO -- 10 PAES -- 11 SPEA2 -- 12 Computational Experiments -- 13 Conclusions -- References -- Multi-objective Portfolio Optimization Problem with Trapezoidal Fuzzy Parameters -- 1 Introduction -- 2 Elements of Fuzzy Theory -- 2.1 Fuzzy Sets -- 2.2 Generalized Fuzzy Numbers -- 2.3 Addition Operator -- 2.4 Graded Mean Integration (GMI) -- 2.5 Order Relation in the Set of the Trapezoidal Fuzzy Numbers -- 2.6 Pareto Dominance -- 3 Multi-objective Portfolio Optimization Problem with Trapezoidal Fuzzy Parameters -- 4 Proposal Algorithm T-NSGA-II. 4.1 Representation of the Solutions -- 4.2 Evaluating the Solutions -- 4.3 One-Point Crossover Operator -- 4.4 Uniform Mutation Operator -- 4.5 Initial Population -- 4.6 Population Sorting -- 4.7 No-Dominated Sorting -- 4.8 Calculating the Crowding Distance (Deb et al. 2000) -- 4.9 Calculating the Spatial Spread Deviation (SSD) (Santiago et al. 2019) -- 4.10 Pseudocode of the T-NSGA-II Algorithm -- 5 Proposed Strategy to Assess the Performance of Multi-objective Algorithms in the Fuzzy Trapezoidal Numbers Domain -- 6 Computational Experiments -- 7 Conclusions -- References -- A Study on the Use of Hyper-heuristics Based on Meta-Heuristics for Dynamic Optimization -- 1 Introduction -- 2 Background and Definitions -- 2.1 Dynamic Multi-objective Optimization Problem -- 2.2 Dynamic Multi-objective Evolutionary Algorithm -- 2.3 Hyper-heuristic -- 2.4 Indicators to Evaluate DMOEAs Performance Over DMOPs -- 3 Relevant Properties to Consider from DMOPs -- 3.1 Objective Function -- 3.2 Decision Variables -- 3.3 Constraints -- 4 Known Hyper-heuristic Approaches Towards Solving DOPs -- 5 Proposed Checklist and Design Guide for Dynamic Hyper-heuristics -- 6 Case Studies Using the Proposed Guide and Checklist -- 6.1 Case Study 1 -- 6.2 Case Study 2 -- 7 Conclusions and Future Work -- References -- On the Adequacy of a Takagi-Sugeno-Kang Protocol as an Empirical Identification Tool for Sigmoidal Allometries in Geometrical Space -- 1 Introduction -- 2 Methods -- 2.1 Model of Complex Allometry -- 2.2 TSK Fuzzy Model -- 2.3 Data -- 2.4 Reproducibility Assessment -- 2.5 TSK Identification Procedures -- 2.6 Piecewise-Linear Schemes -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- A New Hybrid Method Based on ACO and PSO with Fuzzy Dynamic Parameter Adaptation for Modular Neural Networks Optimization -- 1 Introduction -- 2 Proposed Method. 2.1 Ant System and ACO Algorithm. |
Record Nr. | UNINA-9910483557103321 |
Cham, Switzerland : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Handbook for Management of Threats : Security and Defense, Resilience and Optimal Strategies / / edited by Konstantinos P. Balomenos, Antonios Fytopoulos, Panos M. Pardalos |
Autore | Balomenos Konstantinos P |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (541 pages) |
Disciplina | 363.348 |
Altri autori (Persone) |
FytopoulosAntonios
PardalosPanos M |
Collana | Springer Optimization and Its Applications |
Soggetto topico |
Mathematical optimization
Calculus of variations Politics and war Mathematical models Calculus of Variations and Optimization Military and Defence Studies Mathematical Modeling and Industrial Mathematics Optimització matemàtica Càlcul de variacions |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-39542-5 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Future threats - creating a resilient society (Fytopoulos) -- Managing environmental threats: integrating nature-related risks into investment decisions and the financial system (Kerckhoven) -- Defense Critical Supply Chain Networks and Risk Management with the Inclusion of Labor: Dynamics and Quantification of Performance and the Ranking of Nodes and Links (Nagurney) -- Facing Shortages – Practical Strategies to Improve Supply Chain Resilience (Kalaitzi) -- Critical infrastructure detection during an evacuation with alternative fuel vehicles (Vogiatzis) -- Risk assessment and identification methodology for the defense industry in times of crisis - decision making (Sanders) -- Quantum Computers – The Need for a New Cryptographic Strategy (Britta) -- On the way to coastal community resilience under tsunami threat (Pelinovsky) -- Transnational Terrorism as a Threat - Cross border threats (Wright) -- Resilience against Hybrid Threats - Empowered by emerging technologies – A study based on Russian invasion of Ukraine (Jasper) -- Earthquakes - Management of threats, a holistic approach (Agapaki) -- Efficiency Evaluation of Regions’ Firefighting Measures by Data Envelopment Analysis (Demin) -- Superposition Principle for Tornado Prediction (Aleskerov) -- A Network-Based Risk-Averse Approach to Optimizing the Security of a Nuclear Facility (Butenko) -- Post-Disaster Damage Assessment by using Drones in a Remote Communication Setting (Balcik) -- Identifying critical nodes in a network (Arulselvan) -- Machine learning-based rumor controlling (Du) -- Strategic Communication as a mean for countering Hybrid Threats (Balomenos) -- The Integrated approach in countering contemporary security and defence threats (Bellou) -- European Union and NATO Cooperation in Hybrid Threats (Kostarakos) -- Hybrid Threats: A European Response (Anagnostakis) -- Integrated Development Environment using M&S and AI for Crisis Management E&T (Nikolov) -- Civil-Military Cooperation for the countering of threats – Protection of civilians during the development of a threat (Porath) -- The Psychological Dynamics of Leadership Amid a Crisis (Pasmore). |
Record Nr. | UNINA-9910799241803321 |
Balomenos Konstantinos P
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
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Lo trovi qui: Univ. Federico II | ||
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Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging : Mathematical Imaging and Vision / / edited by Ke Chen, Carola-Bibiane Schönlieb, Xue-Cheng Tai, Laurent Younes |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (1981 pages) |
Disciplina | 006.37 |
Soggetto topico |
Mathematics - Data processing
Image processing - Digital techniques Computer vision Mathematical optimization Mathematical analysis Neural networks (Computer science) Computational Mathematics and Numerical Analysis Computer Imaging, Vision, Pattern Recognition and Graphics Optimization Analysis Mathematical Models of Cognitive Processes and Neural Networks Models matemàtics Visió per ordinador Diagnòstic per la imatge Optimització matemàtica |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-98661-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 1. An Overview of SaT Segmentation Methodology and Its Applications in Image Processing -- 2. Analysis of different losses for deep learning image colorization -- 3. Blind phase retrieval with fast algorithms -- 4. Bregman Methods for Large-Scale Optimisation with Applications in Imaging -- 5. Connecting Hamilton-Jacobi Partial Differential Equations with Maximum a Posteriori and Posterior Mean Estimators for Some Non-convex Priors -- 6. Convex non-Convex Variational Models -- 7. Data-Informed Regularization for Inverse and Imaging Problems -- 8. Diffraction Tomography, Fourier Reconstruction, and Full Waveform Inversion -- 9. Domain Decomposition for Non-smooth (in Particular TV) Minimization -- 10. Fast numerical methods for image segmentation models. |
Record Nr. | UNINA-9910674347403321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
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Lo trovi qui: Univ. Federico II | ||
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Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging [[electronic resource] ] : Mathematical Imaging and Vision / / edited by Ke Chen, Carola-Bibiane Schönlieb, Xue-Cheng Tai, Laurent Younces |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
Descrizione fisica | 1 online resource (20 illus., 10 illus. in color.) |
Disciplina | 518 |
Soggetto topico |
Computer mathematics
Optical data processing Mathematical optimization Partial differential equations Neural networks (Computer science) Computational Mathematics and Numerical Analysis Computer Imaging, Vision, Pattern Recognition and Graphics Optimization Partial Differential Equations Mathematical Models of Cognitive Processes and Neural Networks Models matemàtics Visió per ordinador Diagnòstic per la imatge Optimització matemàtica |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-03009-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910483401003321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging [[electronic resource] ] : Mathematical Imaging and Vision / / edited by Ke Chen, Carola-Bibiane Schönlieb, Xue-Cheng Tai, Laurent Younces |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
Descrizione fisica | 1 online resource (20 illus., 10 illus. in color.) |
Disciplina | 518 |
Soggetto topico |
Computer mathematics
Optical data processing Mathematical optimization Partial differential equations Neural networks (Computer science) Computational Mathematics and Numerical Analysis Computer Imaging, Vision, Pattern Recognition and Graphics Optimization Partial Differential Equations Mathematical Models of Cognitive Processes and Neural Networks Models matemàtics Visió per ordinador Diagnòstic per la imatge Optimització matemàtica |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-03009-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996466558203316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Handbook of Metaheuristics / / edited by Michel Gendreau, Jean-Yves Potvin |
Edizione | [3rd ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (610 pages) |
Disciplina | 658.4034 |
Collana | International Series in Operations Research & Management Science |
Soggetto topico |
Operations research
Management science Computer science - Mathematics Operations Research and Decision Theory Operations Research, Management Science Mathematical Applications in Computer Science Optimització matemàtica Investigació operativa |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-319-91086-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 1. Simulated Annealing: From Basics to Applications -- Chapter 2. Tabu Search -- Chapter 3. Variable Neighborhood Search -- Chapter 4. Large Neighborhood Search -- Chapter 5. Iterated Local Search: Framework and Applications -- Chapter 6. Greedy Randomized Adaptive Search Procedures: Advances and Extensions -- Chapter 7. Intelligent Multi-Start Methods -- Chapter 8. Next Generation Genetic Algorithms: A User’s Guide and Tutorial -- Chapter 9. An Accelerated Introduction to Memetic Algorithms -- Chapter 10. Ant Colony Optimization: Overview and Recent Advances -- Chapter 11. Swarm Intelligence -- Chapter 12. Metaheuristic Hybrids -- Chapter 13. Parallel Metaheuristics and Cooperative Search -- Chapter 14. A Classification of Hyper-heuristic Approaches – Revisited -- Chapter 15. Reactive Search Optimization: Learning while Optimizing -- Chapter 16. Stochastic Search in Metaheuristics -- Chapter 17. Automated Design of Metaheuristic Algorithms -- Chapter 18. Computational Comparison of Metaheuristics. |
Record Nr. | UNINA-9910337800503321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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High-Dimensional Optimization and Probability [[electronic resource] ] : With a View Towards Data Science / / edited by Ashkan Nikeghbali, Panos M. Pardalos, Andrei M. Raigorodskii, Michael Th. Rassias |
Edizione | [1st ed. 2022.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
Descrizione fisica | 1 online resource (417 pages) |
Disciplina | 519.3 |
Collana | Springer Optimization and Its Applications |
Soggetto topico |
Mathematical optimization
Probabilities Business information services Mathematics Optimization Applied Probability IT in Business Applications of Mathematics Optimització matemàtica Probabilitats |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-00832-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Projection of a point onto a convex set via Charged Balls Method (E. Abbasov ) -- Towards optimal sampling for learning sparse approximations in high dimensions (Adcock) -- Recent Theoretical Advances in Non-Convex Optimization (Gasnikov) -- Higher Order Embeddings for the Composition of the Harmonic Projection and Homotopy Operators (Ding) -- Codifferentials and Quasidifferentials of the Expectation of Nonsmooth Random Integrands and Two-Stage Stochastic Programming (M.V. Dolgopolik) -- On the Expected Extinction Time for the Adjoint Circuit Chains associated with a Random Walk with Jumps in Random Environments (Ganatsiou) -- A statistical learning theory approach for the analysis of the trade-off between sample size and precision in truncated ordinary least squares (Raciti) -- Recent theoretical advances in decentralized distributed convex optimization (Gasnikov) -- On training set selection in spatial deep learning (M.T. Hendrix) -- Surrogate-Based Reduced Dimension Global Optimization in Process Systems Engineering (Xiang Li) -- A viscosity iterative method with alternated inertial terms for solving the split feasibility problem (Rassias) -- Efficient Location-Based Tracking for IoT Devices Using Compressive Sensing and Machine Learning Techniques (Aboushelbaya) -- Nonsmooth Mathematical Programs with Vanishing Constraints in Banach Spaces (Singh). |
Record Nr. | UNISA-996485662403316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
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Lo trovi qui: Univ. di Salerno | ||
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High-Dimensional Optimization and Probability : With a View Towards Data Science / / edited by Ashkan Nikeghbali, Panos M. Pardalos, Andrei M. Raigorodskii, Michael Th. Rassias |
Edizione | [1st ed. 2022.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
Descrizione fisica | 1 online resource (417 pages) |
Disciplina | 519.3 |
Collana | Springer Optimization and Its Applications |
Soggetto topico |
Mathematical optimization
Probabilities Business information services Mathematics Optimization Applied Probability IT in Business Applications of Mathematics Optimització matemàtica Probabilitats |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-00832-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Projection of a point onto a convex set via Charged Balls Method (E. Abbasov ) -- Towards optimal sampling for learning sparse approximations in high dimensions (Adcock) -- Recent Theoretical Advances in Non-Convex Optimization (Gasnikov) -- Higher Order Embeddings for the Composition of the Harmonic Projection and Homotopy Operators (Ding) -- Codifferentials and Quasidifferentials of the Expectation of Nonsmooth Random Integrands and Two-Stage Stochastic Programming (M.V. Dolgopolik) -- On the Expected Extinction Time for the Adjoint Circuit Chains associated with a Random Walk with Jumps in Random Environments (Ganatsiou) -- A statistical learning theory approach for the analysis of the trade-off between sample size and precision in truncated ordinary least squares (Raciti) -- Recent theoretical advances in decentralized distributed convex optimization (Gasnikov) -- On training set selection in spatial deep learning (M.T. Hendrix) -- Surrogate-Based Reduced Dimension Global Optimization in Process Systems Engineering (Xiang Li) -- A viscosity iterative method with alternated inertial terms for solving the split feasibility problem (Rassias) -- Efficient Location-Based Tracking for IoT Devices Using Compressive Sensing and Machine Learning Techniques (Aboushelbaya) -- Nonsmooth Mathematical Programs with Vanishing Constraints in Banach Spaces (Singh). |
Record Nr. | UNINA-9910586596903321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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