This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number of exercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization.

This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number of exercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization.

FROM THE INTRODUCTION BY MICHELE GALLO COOK......... There are a few things you have to understand about this cookbook before you try any of the recipes. First, my mother was a terrific cook, and I'm not saying that just because she was my mother. Anyone who came to dinner at our house, and there were quite a few, shared that opinion. She could, with amazing talent, open the refrigerator and create a memorable meal out of almost nothing. This made for great dinners but hard-to-follow recipes My mother rarely wrote anything down, and for the most part, it wasn't until I got married that any of these recipes were written down. About a week before my wedding, I asked my mother to make my favorite foods, and then I followed her around the kitchen, badgering her about what went into what dish, how much and how long it was cooked, etc. I still have that first beat up cookbook with the recipes. I am convinced that some of my mother's recipes can never be duplicated, whether it was the pan she used or a trick of my memory, some things just never come out the same. --Michele Gallo Cook......... .......FROM THE EDITOR/DESIGNER, MARINO AMORUSO....... In a family full of great Italian cooks, Aunt Phil Gallo was by far the best. Felicia Amoruso came to America in 1938 at fifteen-years old from Bisceglie, Italy with her older brother, Vittorio, and her mother, Aurelia. He father had passed away and four of her older siblings, Angela, Marino, Pietro and Giovanna were already in New York. Older brothers Angelo and Francesco had been drafted into the Italian army by Mussolini and could not escape Italy. In 1944 she married a duck farmer from East Patchogue, Long Island named Michael Gallo and they built a wonderful life together until Aunt Phil passed away in 1990. The recipes in the book are by no means everything that Aunt Phil was capable of cooking. She could make hundreds of dishes - all from memory. My cousin Michele, however, has done an absolutely remarkable job in putting this collection together. It features Aunt Phil's best work. Michele makes just about everything in this book as good as her mother did, which is a high compliment, indeed. --Marino Amoruso

Networking Explained 2E offers a comprehensive overview of computer networking, with new chapters and sections to cover the latest developments in the field, including voice and data wireless networking, multimedia networking, and network convergence.
Gallo and Hancock provide a sophisticated introduction to their subject in a clear, readable format. These two top networking experts answer hundreds of questions about hardware, software, standards, and future directions in network technology.
Wireless networks
Convergence of voice and data
Multimedia networking