Braverman Readings in Machine Learning. Key Ideas from Inception to Current State International Conference Commemorating the 40th Anniversary of Emmanuil Braverman's Decease, Boston, MA, USA, April 28-30, 2017, Invited Talks

This state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing machine learning theory.
The 12 revised full papers and 4 short papers included in this volume were presented at the conference "Braverman Readings in Machine Learning: Key Ideas from Inception to Current State" held in Boston, MA, USA, in April 2017, commemorating the 40th anniversary of Emmanuil Braverman's decease. The papers present an overview of some of Braverman's ideas and approaches.
The collection is divided in three parts. The first part bridges the past and the present and covers the concept of kernel function and its application to signal and image analysis as well as clustering. The second part presents a set of extensions of Braverman's work to issues of current interest both in theory and applications of machine learning. The third part includes short essaysby a friend, a student, and a colleague.

Zusammenfassung

This state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing machine learning theory.
The 12 revised full papers and 4 short papers included in this volume were presented at the conference "Braverman Readings in Machine Learning: Key Ideas from Inception to Current State" held in Boston, MA, USA, in April 2017, commemorating the 40th anniversary of Emmanuil Braverman's decease. The papers present an overview of some of Braverman's ideas and approaches.
The collection is divided in three parts. The first part bridges the past and the present and covers the concept of kernel function and its application to signal and image analysis as well as clustering. The second part presents a set of extensions of Braverman's work to issues of current interest both in theory and applications of machine learning. The third part includes short essaysby a friend, a student, and a colleague.

Produktdetails

• Mitarbeit: Lev Rozonoer (Herausgeber), Ilya Muchnik (Herausgeber), Boris Mirkin (Herausgeber)
• Verlag: Springer, Berlin
• Inhalt: Buch
• Produktform: Taschenbuch
• Erscheinungsdatum: 24.08.2018
• Thema: Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Informatik
• EAN: 9783319994918
• ISBN: 978-3-31-999491-8
• Anzahl Seiten: 353
• Illustration: XII, 353 p. 65 illus.
• Abmessung (Verpackung): 15.4 x 23.8 x 2.2 cm
• Gewicht (Verpackung): 558 g
• Serie: Lecture Notes in Computer Science > 11100; Lecture Notes in Artificial Intelligence > 11100
• Themen: Expertensystem, B, Algorithmen und Datenstrukturen, KI, Data Mining, Algorithms, Robotics, Artificial Intelligence, Wahrscheinlichkeitsrechnung und Statistik, Algorithmus, datamining, Intelligenz / Künstliche Intelligenz, Künstliche Intelligenz - AI, Datenverarbeitung / Anwendungen / Mathematik, Statistik, Datenverarbeitung / Anwendungen / Betrieb, Verwaltung, Roboter - Robotik - Industrieroboter, Mathematik / Informatik, Computer, Data Mining (EDV), Wissensbasierte Systeme, Expertensysteme, Wissensbasiertes System, Mathematik für Informatiker, computer science, Supervised Learning, Theory of Computation, probability, Data Mining and Knowledge Discovery, Algorithms & data structures, Mathematical & statistical software, Maths for computer scientists, Mathematical statistics, Probability and Statistics in Computer Science, Algorithm Analysis and Problem Complexity, Expert systems / knowledge-based systems, Support Vector Machines (SVM), ArtificialIntelligence, machinelearning, supervisedlearning, algorithmanalysisandproblemcomplexity, clusteranalysis, SupportVectorMachines(SVM), Multivariatestatistics, semi-supervisedlearning, learningalgorithms, mixturemodeling, clusteringalgorithms, Modelsoflearning, classificationaccuracy, kernelfunction