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[null,"1.","Record Nr.",null,"UNISA996390128503316"]
[null,null,"Autore",null,"Nalson John <1638?-1686.>"]
[null,null,"Titolo",null,"An impartial collection of the great affairs of state, from the beginning of the Scotch rebellion in the year MDCXXXIX. To the murther of King Charles I [[electronic resource] ] : Wherein the first occasions, and the whole series of the late troubles in England, Scotland, & Ireland, are faithfully represented. Taken from authentick records, and methodically digested, by John Nalson, LL.D. Vol. II. Published by his Majesties special command"]
[null,null,"Pubbl/distr/stampa",null,"London, : printed for Tho. Dring, Benj. Tooke, Ch. Harper, Tho. Sawbridge, and Jo. Amery, in Fleet-street, St. Paul's Church-Yard, and Little-Britain, M DC LXXXIII. [1683]"]
[null,null,"Descrizione fisica",null,"[6], xii, 920, [22] p"]
[null,null,"Soggetti",null,"Great Britain History Charles I, 1625-1649 Early works to 1800"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Running title reads: An impartial collection of all the memorable events from the Scotch rebellion to the King's murther."]
[{"$nulls":4},"Reproduction of the original in the Jesus College Library at the University of Cambridge."]
[null,null,null,"Sommario/riassunto","eebo-0069"]
[null,"2.","Record Nr.",null,"UNINA9910300121803321"]
[null,null,"Autore",null,"Nesterov I︠U︡. E."]
[null,null,"Titolo",null,"Lectures on Convex Optimization / / by Yurii Nesterov"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018"]
[null,null,"ISBN",null,"3-319-91578-9"]
[null,null,"Edizione",null,"[2nd ed. 2018.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XXIII, 589 p. 1 illus.)"]
[null,null,"Collana",null,"Springer Optimization and Its Applications, , 1931-6828 ; ; 137"]
[null,null,"Disciplina",null,"519.3"]
[null,null,"Soggetti",null,"Mathematical optimization"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Optimization"]
[{"$nulls":4},"Algorithm Analysis and Problem Complexity"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Introduction -- Part I Black-Box Optimization -- 1 Nonlinear Optimization -- 2 Smooth Convex Optimization -- 3 Nonsmooth Convex Optimization -- 4 Second-Order Methods -- Part II Structural Optimization -- 5 Polynomial-time Interior-Point Methods -- 6 Primal-Dual Model of Objective Function -- 7 Optimization in Relative Scale -- Bibliographical Comments -- Appendix A. Solving some Auxiliary Optimization Problems -- References -- Index."]
[null,null,null,"Sommario/riassunto","This book provides a comprehensive, modern introduction to convex optimization, a field that is becoming increasingly important in applied mathematics, economics and finance, engineering, and computer science, notably in data science and machine learning. Written by a leading expert in the field, this book includes recent advances in the algorithmic theory of convex optimization, naturally complementing the existing literature. It contains a unified and rigorous presentation of the acceleration techniques for minimization schemes of first- and second-order. It provides readers with a full treatment of the smoothing technique, which has tremendously extended the abilities of gradient-type methods. Several powerful approaches in structural optimization, including optimization in relative scale and polynomial-time interior-point methods, are also discussed in detail. Researchers in theoretical optimization as well as professionals working on optimization problems will find this book very useful. It presents many successful examples of how to develop very fast specialized "]
[{"$nulls":4},"minimization algorithms. Based on the author’s lectures, it can naturally serve as the basis for introductory and advanced courses in convex optimization for students in engineering, economics, computer science and mathematics."]