The Chinese economy is growing at an unprecedented speed, and one of the emerging trends is angel investment. It is an area with tremendous potential for growth. Compared with the more mature markets in Western countries, however, angel investing in China is still at an early stage, due to a lack of incentives and insufficient policy support.By delving into existing literature on China's angel investment and conducting interviews with leading angel investors for China and abroad, Prof. Liu Manhong and Dr Wang Jiani — both scholars on and practitioners in the angel investment market — try to provide readers with a detailed picture of China's angel market: What is going on in the market? How should the government formulate relevant polices? And, perhaps more pertinently, what should investors know if they have invested in or are going to enter this market?This book will be very useful for scholars and researchers on China's angel market, as well as those 'angels' who would like to tap its full potential.
Tensor is a natural representation for multi-dimensional data, and tensor computation can avoid possible multi-linear data structure loss in classical matrix computation-based data analysis. This book is intended to provide non-specialists an overall understanding of tensor computation and its applications in data analysis, and benefits researchers, engineers, and students with theoretical, computational, technical and experimental details. It presents a systematic and up-to-date overview of tensor decompositions from the engineer's point of view, and comprehensive coverage of tensor computation based data analysis techniques. In addition, some practical examples in machine learning, signal processing, data mining, computer vision, remote sensing, and biomedical engineering are also presented for easy understanding and implementation. These data analysis techniques may be further applied in other applications on neuroscience, communication, psychometrics, chemometrics, biometrics, quantum physics, quantum chemistry, etc. The discussion begins with basic coverage of notations, preliminary operations in tensor computations, main tensor decompositions and their properties. Based on them, a series of tensor-based data analysis techniques are presented as the tensor extensions of their classical matrix counterparts, including tensor dictionary learning, low rank tensor recovery, tensor completion, coupled tensor analysis, robust principal tensor component analysis, tensor regression, logistical tensor regression, support tensor machine, multilinear discriminate analysis, tensor subspace clustering, tensor-based deep learning, tensor graphical model and tensor sketch. The discussion also includes a number of typical applications with experimental results, such as image reconstruction, image enhancement, data fusion, signal recovery, recommendation system, knowledge graph acquisition, traffic flow prediction, link prediction, environmental prediction, weather forecasting, background extraction, human pose estimation, cognitive state classification from fMRI, infrared small target detection, heterogeneous information networks clustering, multi-view image clustering, and deep neural network compression.
Tensor is a natural representation for multi-dimensional data, and tensor computation can avoid possible multi-linear data structure loss in classical matrix computation-based data analysis. This book is intended to provide non-specialists an overall understanding of tensor computation and its applications in data analysis, and benefits researchers, engineers, and students with theoretical, computational, technical and experimental details. It presents a systematic and up-to-date overview of tensor decompositions from the engineer's point of view, and comprehensive coverage of tensor computation based data analysis techniques. In addition, some practical examples in machine learning, signal processing, data mining, computer vision, remote sensing, and biomedical engineering are also presented for easy understanding and implementation. These data analysis techniques may be further applied in other applications on neuroscience, communication, psychometrics, chemometrics, biometrics, quantum physics, quantum chemistry, etc. The discussion begins with basic coverage of notations, preliminary operations in tensor computations, main tensor decompositions and their properties. Based on them, a series of tensor-based data analysis techniques are presented as the tensor extensions of their classical matrix counterparts, including tensor dictionary learning, low rank tensor recovery, tensor completion, coupled tensor analysis, robust principal tensor component analysis, tensor regression, logistical tensor regression, support tensor machine, multilinear discriminate analysis, tensor subspace clustering, tensor-based deep learning, tensor graphical model and tensor sketch. The discussion also includes a number of typical applications with experimental results, such as image reconstruction, image enhancement, data fusion, signal recovery, recommendation system, knowledge graph acquisition, traffic flow prediction, link prediction, environmental prediction, weather forecasting, background extraction, human pose estimation, cognitive state classification from fMRI, infrared small target detection, heterogeneous information networks clustering, multi-view image clustering, and deep neural network compression.
The Chinese economy is growing at an unprecedented speed, and one of the emerging trends is angel investment. It is an area with tremendous potential for growth. Compared with the more mature markets in Western countries, however, angel investing in China is still at an early stage, due to a lack of incentives and insufficient policy support.By delving into existing literature on China's angel investment and conducting interviews with leading angel investors for China and abroad, Prof. Liu Manhong and Dr Wang Jiani — both scholars on and practitioners in the angel investment market — try to provide readers with a detailed picture of China's angel market: What is going on in the market? How should the government formulate relevant polices? And, perhaps more pertinently, what should investors know if they have invested in or are going to enter this market?This book will be very useful for scholars and researchers on China's angel market, as well as those 'angels' who would like to tap its full potential.
What happens when East travels West? In today’s increasingly globalized world, these collisions are becoming increasingly common in universities– especially due to the growth of migratory students . As the largest international population studying abroad in the world, Chinese students’ learning experience in an intercultural environment calls for more attention. This book covers an array of problems common to Chinese students studying abroad and explores how these students academically adjust to an intercultural environment. It also highlights how they familiarize themselves with the education system, ranging from the types of courses, academic tasks and examinations to the structure of the education as a whole in the host country, as they negotiate the gulf between academic expectations at home versus those in the host university environment and communicate with domestic lecturers and students.
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