MM Optimization Algorithms
iul. 2016 · Other Titles in Applied Mathematics Cartea 145 · SIAM
5,0star
O recenziereport
Carte electronică
232
Pagini
family_home
Eligibilă
info
reportEvaluările și recenziile nu sunt verificate Află mai multe
Despre această carte electronică
MM Optimization Algorithms offers an overview of the MM principle, a device for deriving optimization algorithms satisfying the ascent or descent property. These algorithms can separate the variables of a problem, avoid large matrix inversions, linearize a problem, restore symmetry, deal with equality and inequality constraints gracefully, and turn a nondifferentiable problem into a smooth problem.
The author presents the first extended treatment of MM algorithms, which are ideal for high-dimensional optimization problems in data mining, imaging, and genomics; derives numerous algorithms from a broad diversity of application areas, with a particular emphasis on statistics, biology, and data mining; and summarizes a large amount of literature that has not reached book form before.
The author presents the first extended treatment of MM algorithms, which are ideal for high-dimensional optimization problems in data mining, imaging, and genomics; derives numerous algorithms from a broad diversity of application areas, with a particular emphasis on statistics, biology, and data mining; and summarizes a large amount of literature that has not reached book form before.
Evaluări și recenzii
5,0
O recenzie
Despre autor
Kenneth Lange is the Rosenfeld Professor of Computational Genetics, and a faculty member in the Departments of Biomathematics, Human Genetics and Statistics, at the University of California, Los Angeles. He has held appointments at the University of New Hampshire, Massachusetts Institute of Technology, Harvard University, the University of Michigan, the University of Helsinki and Stanford University. He is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Institute for Medical and Biomedical Engineering. He won the Snedecor Award from the Joint Statistical Societies in 1993 and gave a platform presentation at the 2015 International Congress of Mathematicians. His research interests include human genetics, population modeling, biomedical imaging, computational statistics, optimization theory, and applied stochastic processes. He has published four previous books: Mathematical and Statistical Methods for Genetic Analysis, Numerical Analysis for Statisticians, Applied Probability, and Optimization, all in second editions.
Evaluează cartea electronică
Spune-ne ce crezi.
Informații despre lectură
Smartphone-uri și tablete
Instalează aplicația Cărți Google Play pentru Android și iPad/iPhone. Se sincronizează automat cu contul tău și poți să citești online sau offline de oriunde te afli.
Laptopuri și computere
Poți să asculți cărțile audio achiziționate pe Google Play folosind browserul web al computerului.
Dispozitive eReader și alte dispozitive
Ca să citești pe dispozitive pentru citit cărți electronice, cum ar fi eReaderul Kobo, trebuie să descarci un fișier și să îl transferi pe dispozitiv. Urmează instrucțiunile detaliate din Centrul de ajutor pentru a transfera fișiere pe dispozitivele eReader compatibile.
