Hui Zou

In this volume, Hui Zou analyzes historical, architectural, visual, literary, and philosophical perspectives on the Western-styled garden that formed part of the great Yuanming Yuan complex in Beijing, constructed during the Qing dynasty. Designed and built in the late eighteenth century by Italian and French Jesuits, the garden described in this book was a wonderland of multistoried buildings, fountains, labyrinths, and geometrical hills. It even included an open-air theater. Through detailed examination of historical literature and representations, Zou analyzes the ways in which the Jesuits accommodated their design within the Chinese cultural context. He shows how an especially important element of their approach was the application of a linear perspective-the "line-method"-to create the jing, the Chinese concept of the bounded bright view of a garden scene. Hui Zou's book demonstrates how Jesuit metaphysics fused with Chinese cosmology and broadens our understanding of cultural and religious encounters in early Chinese modernity. It presents an intriguing reflection on the interaction between Western metaphysics and the poetical tradition of Chinese culture. The volume will be of interest to scholars and students in a variety of fields, including literature, philosophy, architecture, landscape and urban studies, and East-West comparative cultural studies.

A Jesuit Garden in Beijing and Early Modern Chinese Culture

In this volume, Hui Zou analyzes historical, architectural, visual, literary, and philosophical perspectives on the Western-styled garden that formed part of the great Yuanming Yuan complex in Beijing, constructed during the Qing dynasty. Designed and built in the late eighteenth century by Italian and French Jesuits, the garden described in this book was a wonderland of multistoried buildings, fountains, labyrinths, and geometrical hills. It even included an open-air theater. Through detailed examination of historical literature and representations, Zou analyzes the ways in which the Jesuits accommodated their design within the Chinese cultural context. He shows how an especially important element of their approach was the application of a linear perspective the "line-method"-to create the jing, the Chinese concept of the bounded bright view of a garden scene. Hui Zou's book demonstrates how Jesuit metaphysics fused with Chinese cosmology and broadens our understanding of cultural and religious encounters in early Chinese modernity. It presents an intriguing reflection on the interaction between Western metaphysics and the poetical tradition of Chinese culture. The volume will be of interest to scholars and students in a variety of fields, including literature, philosophy, architecture, landscape and urban studies, and East-West comparative cultural studies.

Jianqing Fan

Cun-Hui Zhang

Runze Li

Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.

Hui Zou

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