Optinformatics evolutionary learning optimization par feng liang (16 résultats)
Langue : anglais
Edité par Springer, 2021
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture rigide
Vendeur : StainesBook, Weybridge, SURRE, Royaume-UniStainesBook
Contacter le vendeurVendeur avec une évaluation de 1 étoilesEtat: Neuf
EUR 89,23
EUR 35,11 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.
Langue : anglais
Edité par Springer, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
Vendeur : Ria Christie Collections, Uxbridge, Royaume-UniRia Christie Collections
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 115,02
EUR 14,02 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New. In.
Langue : anglais
Edité par Springer, 2021
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture rigide
Vendeur : Ria Christie Collections, Uxbridge, Royaume-UniRia Christie Collections
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 116,78
EUR 14,02 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New. In.
Langue : anglais
Edité par Springer, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
Vendeur : Books Puddle, New York, NY, Etats-UnisBooks Puddle
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 142,42
EUR 3,46 expéditionExpédition nationale : Etats-UnisQuantité disponible : 4 disponible(s)
Etat : New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Langue : anglais
Edité par Springer Nature, 2021
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture rigide
Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 153,02
EUR 11,70 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 2 disponible(s)
Hardcover. Etat : Brand New. 152 pages. 9.25x6.10x9.21 inches. In Stock.
Autres imagesLangue : anglais
Edité par Springer, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
Vendeur : preigu, Osnabrück, Allemagnepreigu
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 95,25
EUR 70,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 5 disponible(s)
Taschenbuch. Etat : Neu. Optinformatics in Evolutionary Learning and Optimization | Liang Feng (u. a.) | Taschenbuch | Adaptation, Learning, and Optimization | viii | Englisch | 2022 | Springer | EAN 9783030709228 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann…[at]springer[dot]com | Anbieter: preigu.
Langue : anglais
Edité par Springer International Publishing, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 106,99
EUR 61,21 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain learning in…vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics.Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process.The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning.
Langue : anglais
Edité par Springer International Publishing, 2021
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 106,99
EUR 62,01 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain learning in vehicle… route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics.Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process.The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning.
Langue : anglais
Edité par Springer International Publishing Mrz 2022, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
- impression à la demande
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 106,99
EUR 23,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 2 disponible(s)
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-dom…ain learning in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics.Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process.The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning. 152 pp. Englisch.
Langue : anglais
Edité par Springer International Publishing Mrz 2021, 2021
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture rigide
- impression à la demande
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 106,99
EUR 23,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 2 disponible(s)
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain lea…rning in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics.Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process.The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning. 152 pp. Englisch.
Langue : anglais
Edité par Springer, Berlin|Springer International Publishing|Springer, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
- impression à la demande
Vendeur : moluna, Greven, Allemagnemoluna
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 92,27
EUR 48,99 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, incl…uding inter-domain .
Langue : anglais
Edité par Springer International Publishing, 2021
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture rigide
- impression à la demande
Vendeur : moluna, Greven, Allemagnemoluna
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 92,27
EUR 48,99 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Summarizes recent algorithmic advances toward realizing the notion of optinformatics in evolutionary learning and optimizationContains a variety of practical applications, including inter-domain learning in vehicle route…planning, data-driven tech.
Langue : anglais
Edité par Springer, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
- impression à la demande
Vendeur : Majestic Books, Hounslow, Royaume-UniMajestic Books
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 147,47
EUR 7,61 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 4 disponible(s)
Etat : New. Print on Demand.
Langue : anglais
Edité par Springer, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
- impression à la demande
Vendeur : Biblios, frankfurt am main, HESSE, AllemagneBiblios
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 150,94
EUR 9,95 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 4 disponible(s)
Etat : New. PRINT ON DEMAND.
Langue : anglais
Edité par Springer, Palgrave Macmillan Mär 2021, 2021
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture rigide
- impression à la demande
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagnebuchversandmimpf2000
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 106,99
EUR 60,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain learnin…g in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics.Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process.The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 152 pp. Englisch.
Langue : anglais
Edité par Springer, Palgrave Macmillan Mär 2022, 2022
Série : Livre 12 sur 12 - Adaptation, Learning, and Optimization
- Couverture souple
- impression à la demande
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagnebuchversandmimpf2000
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 106,99
EUR 60,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain…learning in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics.Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process.The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 152 pp. Englisch.
