Publisher Summary The total least squares (TLS) method is one of the several linear
parameter estimation techniques that have been devised to compensate for data errors. One …

The linear least squares problem is a computational problem of primary importance in many
applications. Assume for example that one wants to fit a linear mathematical model to given …

This survey describes probabilistic algorithms for linear algebraic computations, such as
factorizing matrices and solving linear systems. It focuses on techniques that have a proven …

A new method for automatic indexing and retrieval is described. The approach is to take
advantage of implicit higher‐order structure in the association of terms with documents …

How do people know as much as they do with as little information as they get? The problem
takes many forms; learning vocabulary from text is an especially dramatic and convenient …

Vector‐based models of word meaning have become increasingly popular in cognitive
science. The appeal of these models lies in their ability to represent meaning simply by …

Excerpt More than 25 years have passed since the first edition of this book was published in
1996. Least squares and least-norm problems have become more significant with every …

Since being analyzed by Rokhlin, Szlam, and Tygert and popularized by Halko, Martinsson,
and Tropp, randomized Simultaneous Power Iteration has become the method of choice for …

The Kronecker product has a rich and very pleasing algebra that supports a wide range of
fast, elegant, and practical algorithms. Several trends in scientific computing suggest that …

This book, Eigensystems, is the second volume in a projected five-volume series entitled
Matrix Algorithms. The first volume treated basic decompositions. The three following this …