A complete introduction to recent advances in preprocessing analysis, or kernelization, with extensive examples using a single data set.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Fedor V. Fomin is Professor of Computer Science at the Universitetet i Bergen, Norway. He is known for his work in algorithms and graph theory. He has co-authored two books, Exact Exponential Algorithms (2010) and Parameterized Algorithms (2015), and received the EATCS Nerode prizes in 2015 and 2017 for his work on bidimensionality and Measure and Conquer.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Hardcover. Zustand: new. Hardcover. Preprocessing, or data reduction, is a standard technique for simplifying and speeding up computation. Written by a team of experts in the field, this book introduces a rapidly developing area of preprocessing analysis known as kernelization. The authors provide an overview of basic methods and important results, with accessible explanations of the most recent advances in the area, such as meta-kernelization, representative sets, polynomial lower bounds, and lossy kernelization. The text is divided into four parts, which cover the different theoretical aspects of the area: upper bounds, meta-theorems, lower bounds, and beyond kernelization. The methods are demonstrated through extensive examples using a single data set. Written to be self-contained, the book only requires a basic background in algorithmics and will be of use to professionals, researchers and graduate students in theoretical computer science, optimization, combinatorics, and related fields. This self-contained introduction to kernelization, a rapidly developing area of preprocessing analysis, is for researchers, professionals, and graduate students in computer science and optimization. It includes recent advances in upper and lower bounds and meta-theorems, and demonstrates methods through extensive examples using a single data set. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781107057760
Anbieter: California Books, Miami, FL, USA
Zustand: New. Bestandsnummer des Verkäufers I-9781107057760
Anzahl: Mehr als 20 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. Bestandsnummer des Verkäufers 26376453596
Anzahl: 4 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 369591811
Anzahl: 4 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Bestandsnummer des Verkäufers ria9781107057760_new
Anzahl: Mehr als 20 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. Bestandsnummer des Verkäufers 18376453590
Anzahl: 4 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Hardcover. Zustand: Brand New. 515 pages. 9.50x6.25x1.25 inches. In Stock. This item is printed on demand. Bestandsnummer des Verkäufers __1107057760
Anzahl: 1 verfügbar
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
Hardcover. Zustand: new. Hardcover. Preprocessing, or data reduction, is a standard technique for simplifying and speeding up computation. Written by a team of experts in the field, this book introduces a rapidly developing area of preprocessing analysis known as kernelization. The authors provide an overview of basic methods and important results, with accessible explanations of the most recent advances in the area, such as meta-kernelization, representative sets, polynomial lower bounds, and lossy kernelization. The text is divided into four parts, which cover the different theoretical aspects of the area: upper bounds, meta-theorems, lower bounds, and beyond kernelization. The methods are demonstrated through extensive examples using a single data set. Written to be self-contained, the book only requires a basic background in algorithmics and will be of use to professionals, researchers and graduate students in theoretical computer science, optimization, combinatorics, and related fields. This self-contained introduction to kernelization, a rapidly developing area of preprocessing analysis, is for researchers, professionals, and graduate students in computer science and optimization. It includes recent advances in upper and lower bounds and meta-theorems, and demonstrates methods through extensive examples using a single data set. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9781107057760
Anzahl: 1 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Hardcover. Zustand: Brand New. 515 pages. 9.50x6.25x1.25 inches. In Stock. Bestandsnummer des Verkäufers x-1107057760
Anzahl: 2 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This self-contained introduction to kernelization, a rapidly developing area of preprocessing analysis, is for researchers, professionals, and graduate students in computer science and optimization. It includes recent advances in upper and lower bounds and . Bestandsnummer des Verkäufers 251534939
Anzahl: Mehr als 20 verfügbar