Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.
In this book the authors reduce a wide variety of problems arising in system and control theory to a handful of convex and quasiconvex optimization problems that involve linear matrix inequalities. These optimization problems can be solved using recently developed numerical algorithms that not only are polynomial-time but also work very well in practice; the reduction therefore can be considered a solution to the original problems. This book opens up an important new research area in which convex optimization is combined with system and control theory, resulting in the solution of a large number of previously unsolved problems.
Stephen Boyd was one of the nicest, kindest people I have met in my lifetime, rare in this profession. - Euan Lloyd, film producer of Shalako, The Man Called Noon and The Wild Geese. Joe Cushnan's excellent biography of Stephen Boyd, the forgotten film star and a fellow countryman of mine, fills a disgraceful gap in cinematographic history and should be read by all who are interested in that fascinating subject. - James Ellis, actor in Z Cars, The Billy Plays, etc Stephen Boyd was one of the biggest film stars of the late 1950s and 1960s (The Man Who Never Was, Ben Hur, The Fall of the Roman Empire, Fantastic Voyage, etc), an ordinary boy from Northern Ireland who made a dream journey to Hol...
Heritage Tourism is a core text for 2nd and 3rd year students on tourism and related degrees where the major focus is on heritage modules. It will also serve as an important reference to postgraduate courses that explore key themes implicit within heritage tourism such as conservation, management, interpretation, and authenticity.
This monograph collects in one place the basic deﬁnitions, a careful description of the model, and discussion of how convex optimization can be used in multi-period trading, all in a common notation and framework.
The corpus of literary works shaped by the Renaissance and the Baroque that appeared in Spain during the sixteenth and seventeenth centuries had a transforming effect on writing throughout Europe and left a rich legacy that scholars continue to explore. For four decades after the Spanish Civil War the study of this literature flourished in Great Britain and Ireland, where many of the leading scholars in the field were based. Though this particular 'Golden Age' was followed by a decline for many years, there have recently been signs of a significant revival. The present book seeks to showcase the latest research of established and younger colleagues from Great Britain and Ireland on the Spani...
Principal components analysis (PCA) is a well-known technique for approximating a tabular data set by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets consisting of numerical, Boolean, categorical, ordinal, and other data types. This framework encompasses many well-known techniques in data analysis, such as nonnegative matrix factorization, matrix completion, sparse and robust PCA, k-means, k-SVD, and maximum margin matrix factorization. The method handles heterogeneous data sets, and leads to coherent schemes for compressing, denoising, and imputing missing entries across all data types simultaneously. It also admits a number of interesting interpretations of the low rank factors, which allow clustering of examples or of features. We propose several parallel algorithms for fitting generalized low rank models, and describe implementations and numerical results.