哈布斯堡家族发源于瑞士北部的阿尔高州，并在1020年筑起鹰堡，名为哈布斯堡，并逐渐将势力扩展到莱茵河西岸流域。1273年，哈布斯堡公爵鲁道夫一世当选德意志国王（但未加冕为皇帝）。1282年12月27日鲁道夫一世夺取被波希米亚国王奥托卡二世占有的奥地利与施蒂利希公国，旋即分封于自己的两个儿子阿尔布雷希特与鲁道夫，自此奥地利划归哈布斯堡皇室拥有长达600余年。
鲁道夫一世1291年逝世后，拿骚家族的阿道夫被选举为国王，但因其与英国结盟很快遭到厌弃，鲁道夫一世之子阿尔布雷希特被选为对立国王，并在1298年击败阿道夫，正式登基。1308年，阿尔布雷希特一世被自己的侄子士瓦本的约翰杀害，自此后虽然阿尔布雷希特的次子腓特烈曾被选举为对立国王，并与巴伐利亚的路德维希四世共治，然而其后的100年间哈布斯堡家族的势力开始退缩到以奥地利为主的家族领地，并把南阿尔萨斯、布赖施高（Breisgau）和帝国内的其他一些领地陆续划入治下。14世纪期间，新成立的瑞士联邦不断向德国南部扩张，导致哈布斯堡家族失去祖先建立的鹰堡。自此，哈布斯堡王朝的基地正式由瑞士南部的鹰堡，转移到下奥地利的维也纳，哈布斯堡家族也被称为奥地利家族。

This book describes established and advanced methods for reducing the dimensionality of numerical databases. Each description starts from intuitive ideas, develops the necessary mathematical details, and ends by outlining the algorithmic implementation. The text provides a lucid summary of facts and concepts relating to well-known methods as well as recent developments in nonlinear dimensionality reduction. Methods are all described from a unifying point of view, which helps to highlight their respective strengths and shortcomings. The presentation will appeal to statisticians, computer scientists and data analysts, and other practitioners having a basic background in statistics or computational learning.

In the 1880s, as the European powers were carving up Africa, King Leopold II of Belgium seized for himself the vast and mostly unexplored territory surrounding the Congo River. Carrying out a genocidal plundering of the Congo, he looted its rubber, brutalized its people, and ultimately slashed its population by ten million--all the while shrewdly cultivating his reputation as a great humanitarian. Heroic efforts to expose these crimes eventually led to the first great human rights movement of the twentieth century, in which everyone from Mark Twain to the Archbishop of Canterbury participated. King Leopold's Ghost is the haunting account of a megalomaniac of monstrous proportions, a man as cunning, charming, and cruel as any of the great Shakespearean villains. It is also the deeply moving portrait of those who fought Leopold: a brave handful of missionaries, travelers, and young idealists who went to Africa for work or adventure and unexpectedly found themselves witnesses to a holocaust. Adam Hochschild brings this largely untold story alive with the wit and skill of a Barbara Tuchman. Like her, he knows that history often provides a far richer cast of characters than any novelist could invent. Chief among them is Edmund Morel, a young British shipping agent who went on to lead the international crusade against Leopold. Another hero of this tale, the Irish patriot Roger Casement, ended his life on a London gallows. Two courageous black Americans, George Washington Williams and William Sheppard, risked much to bring evidence of the Congo atrocities to the outside world. Sailing into the middle of the story was a young Congo River steamboat officer named Joseph Conrad. And looming above them all, the duplicitous billionaire King Leopold II. With great power and compassion, King Leopold's Ghost will brand the tragedy of the Congo--too long forgotten--onto the conscience of the West.

This book provides a fundamental understanding of global illumination algorithms. It discusses a broad class of algorithms for realistic image synthesis and introduces a theoretical basis for the algorithms presented. Topics include: physics of light transport, Monte Carlo methods, general strategies for solving the rendering equation, stochastic path-tracing algorithms such as ray tracing and light tracing, stochastic radiosity including photon density estimation and hierarchical Monte Carlo radiosity, hybrid algorithms, metropolis light transport, irradiance caching, photon mapping and instant radiosity, beyond the rendering equation, image display and human perception. If you want to design and implement a global illumination rendering system or need to use and modify an existing system for your specific purpose, this book will give you the tools and the understanding to do so.

A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.

This first volume, a three-part introduction to the subject, is intended for students with a beginning knowledge of mathematical analysis who are motivated to discover the ideas that shape Fourier analysis. It begins with the simple conviction that Fourier arrived at in the early nineteenth century when studying problems in the physical sciences - that an arbitrary function can be written as an infinite sum of the most basic trigonometric functions. The first part implements this idea in terms of notions of convergence and summability of Fourier series, while highlighting applications such as the isoperimetric inequality and equidistribution. The second part deals with the Fourier transform and its applications to classical partial differential equations and the Radon transform; a clear introduction to the subject serves to avoid technical difficulties. The book closes with Fourier theory for finite abelian groups, which is applied to prime numbers in arithmetic progression. In organizing their exposition, the authors have carefully balanced an emphasis on key conceptual insights against the need to provide the technical underpinnings of rigorous analysis. Students of mathematics, physics, engineering and other sciences will find the theory and applications covered in this volume to be of real interest. "The Princeton Lectures in Analysis" represents a sustained effort to introduce the core areas of mathematical analysis while also illustrating the organic unity between them. Numerous examples and applications throughout its four planned volumes, of which "Fourier Analysis" is the first, highlight the far-reaching consequences of certain ideas in analysis to other fields of mathematics and a variety of sciences. Stein and Shakarchi move from an introduction addressing "Fourier" series and integrals to in-depth considerations of complex analysis; measure and integration theory, and Hilbert spaces; and, finally, further topics such as functional analysis, distributions and elements of probability theory.