"Numerous and large dimensional data is now a default setting in modern machine learning (ML). Standard ML algorithms, starting with kernel methods such as support vector machines and graph-based methods like the PageRank algorithm, were however initially designed out of small d…
"Numerous and large dimensional data is now a default setting in modern machine learning (ML). Standard ML algorithms, starting with kernel methods such as support vector machines and graph-based methods like the PageRank algorithm, were however initially designed out of small d…
This book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentration and universality phenomena. This enables a precise understanding, and possible improvements, of the core mechanisms a…
This book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentration and universality phenomena. This enables a precise understanding, and possible improvements, of the core mechanisms a…
This book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentration and universality phenomena. This enables a precise understanding, and possible improvements, of the core mechanisms a…
This balanced and comprehensive study presents the theory, methods and applications of matrix analysis in a new theoretical framework, allowing readers to understand second-order and higher-order matrix analysis in a completely new light. Alongside the core subjects in matrix an…
This balanced and comprehensive study presents the theory, methods and applications of matrix analysis in a new theoretical framework, allowing readers to understand second-order and higher-order matrix analysis in a completely new light. Alongside the core subjects in matrix an…
This volume is a tribute to Professor Dietrich von Rosen on the occasion of his 65th birthday. It contains a collection of twenty original papers. The contents of the papers evolve around multivariate analysis and random matrices with topics such as high-dimensional analysis, go…
by Kloeden, Peter E., Deakin University, Palmer, Kenneth J., (Kenneth James), International workshop on the approximation and computation of complicated dynamical behavior, Deakin University)
fromContemporary mathematics (American Mathematical Society)
La quatrième de couv. indique : "Cet ouvrage est consacré a l'étude de l'espace vectoriel Mn (K) des matrices carrées a coefficients réels ou complexes du point de vue algébrique et topologique, préalable nécessaire a tout cours d'analyse numérique. La synthèse réalisée par l'au…
Outlining 20 tricks for linear statistical models, this text covers topics such as generalised inverses, the rank cancellation rule and diagonalisation and the Schur complement.
