Kernel of the Kernel

This authoritative book acts as a guide to understanding maize kernel development. Written by a team of experts, it covers topics spanning pre- and post-fertilization events, embryo and endosperm deve

This book describes computational problems related to kernel density estimation (KDE) – one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-ba

Digital Signal Processing with Kernel Methods will review the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. In additio

This text provides a masterful and systematic treatment of all the basic analytic and geometric aspects of Bergman's classic theory of the kernel and its invariance properties. These include calculati

An all-new Popcorn Shop Mystery bursts on the scene, featuring gourmet popcorn entrepreneur Rebecca Anderson and her poodle Sprocket.Opening a gourmet popcorn shop was never on Rebecca Anderson’s buck

Reproducing kernel Hilbert spaces have developed into an important tool in many areas, especially statistics and machine learning, and they play a valuable role in complex analysis, probability, group representation theory, and the theory of integral operators. This unique text offers a unified overview of the topic, providing detailed examples of applications, as well as covering the fundamental underlying theory, including chapters on interpolation and approximation, Cholesky and Schur operations on kernels, and vector-valued spaces. Self-contained and accessibly written, with exercises at the end of each chapter, this unrivalled treatment of the topic serves as an ideal introduction for graduate students across mathematics, computer science, and engineering, as well as a useful reference for researchers working in functional analysis or its applications.

This book deals with the partial differential equations and some of their applications. The book consists of four parts. The first part presents some background material and an introduction

In an attempt to introduce application scientists and graduate students to the exciting topic of positive definite kernels and radial basis functions, this book presents modern theoretical results on

Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent yearsThis book covers kernel analysis topics ranging from the fundamental theo

Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate student

Linux Kernel Networking takes you on a guided in-depth tour of the current Linux networking implementation and the theory behind it. Linux kernel networking is a complex topic, so the book won't burde

This text provides a masterful and systematic treatment of all the basic analytic and geometric aspects of Bergman's classic theory of the kernel and its invariance properties. These include calculati

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recogniti

The book covers theoretical questions including the latest extension of the formalism, and computational issues and focuses on some of the more fruitful and promising applications, including statistic

Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. This book

Describes the process of corn production, including planting the kernels, tending and harvesting the crop, and transporting the corn to the grocery store so that it may be bought and eaten.

Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins w

The number of security countermeasures against user-land exploitation is on the rise. Because of this, kernel exploitation is becoming much more popular among exploit writers and attackers. Playing wi