1 Introduction -- 2 Prerequisites from Matrix Analysis -- 3 Multivariate Distributions and Moments -- 4 Dimensionality Reduction -- 5 Classification and Clustering -- 6 Support Vector Machines -- 7 Machine Learning -- Index. This book introduces the basic methodologies for succ…
This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral…
This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral…
The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed…