1.

Record Nr.

UNINA990005648950403321

Titolo

Dom Deschamps et sa métaphysique : religion et contestation au XVIII siècle / ouvrage publié sous la direction de Jacques d'Hondt

Pubbl/distr/stampa

Paris, : Presses universitaires de France, 1974

Descrizione fisica

248 p. ; 22 cm

Collana

Bibliothèque de philosophie contemporaine

Disciplina

110

194

Locazione

FLFBC

NAP03

SDI

Collocazione

P.1 FRM 466

P.1 FRM 466 BIS

SDI-2KG 370

DFT A10 HONJ 01

Lingua di pubblicazione

Francese

Formato

Materiale a stampa

Livello bibliografico

Monografia



2.

Record Nr.

UNINA9910437864403321

Autore

Lange Kenneth

Titolo

Optimization / / by Kenneth Lange

Pubbl/distr/stampa

New York, NY : , : Springer New York : , : Imprint : Springer, , 2013

ISBN

1-4614-5838-2

Edizione

[2nd ed. 2013.]

Descrizione fisica

1 online resource (540 p.)

Collana

Springer Texts in Statistics, , 2197-4136 ; ; 95

Disciplina

519.3

Soggetti

Statistics

Mathematical optimization

Operations research

Statistical Theory and Methods

Optimization

Operations Research and Decision Theory

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di contenuto

Elementary Optimization -- The Seven C’s of Analysis -- The Gauge Integral -- Differentiation -- Karush-Kuhn-Tucker Theory -- Convexity -- Block Relaxation -- The MM Algorithm -- The EM Algorithm -- Newton’s Method and Scoring -- Conjugate Gradient and Quasi-Newton -- Analysis of Convergence -- Penalty and Barrier Methods -- Convex Calculus -- Feasibility and Duality -- Convex Minimization Algorithms -- The Calculus of Variations -- Appendix: Mathematical Notes -- References -- Index.

Sommario/riassunto

Finite-dimensional optimization problems occur throughout the mathematical sciences. The majority of these problems cannot be solved analytically. This introduction to optimization attempts to strike a balance between presentation of mathematical theory and development of numerical algorithms. Building on students’ skills in calculus and linear algebra, the text provides a rigorous exposition without undue abstraction. Its stress on statistical applications will be especially appealing to graduate students of statistics and biostatistics. The intended audience also includes students in applied mathematics,



computational biology, computer science, economics, and physics who want to see rigorous mathematics combined with real applications.   In this second edition, the emphasis remains on finite-dimensional optimization. New material has been added on the MM algorithm, block descent and ascent, and the calculus of variations. Convex calculus is now treated in much greater depth.  Advanced topics such as the Fenchel conjugate, subdifferentials, duality, feasibility, alternating projections, projected gradient methods, exact penalty methods, and Bregman iteration will equip students with the essentials for understanding modern data mining techniques in high dimensions.