Yipeng Liu – författare
1 258 kr
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Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing. This reference is ideal for students, researchers and industry developers who want to understand and use tensor-based data processing theories and methods.
As a higher-order generalization of a matrix, tensor-based processing can avoid multi-linear data structure loss that occurs in classical matrix-based data processing methods. This move from matrix to tensors is beneficial for many diverse application areas, including signal processing, computer science, acoustics, neuroscience, communication, medical engineering, seismology, psychometric, chemometrics, biometric, quantum physics and quantum chemistry.
Provides a complete reference on classical and state-of-the-art tensor-based methods for data processing Includes a wide range of applications from different disciplines Gives guidance for their application1 751 kr
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Innovation and Entrepreneurship Education
International Comparative Perspectives from Asia and Europe
2 254 kr
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Innovation and Entrepreneurship Education
International Comparative Perspectives from Asia and Europe
418 kr
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Innovation and Entrepreneurship Education
International Comparative Perspectives from Asia and Europe
418 kr
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2 289 kr
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3 286 kr
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761 kr
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With chapters covering key topics within multiple domains of management and organization studies, the Research Handbook of International Talent Management explores the topic in innovative entrepreneurial enterprises to international businesses. It also examines how talent management relates to sustainability and public management, providing in depth coverage of the field for an interdisciplinary approach to what is one of the grand contemporary challenges facing the global economy today.
This Research Handbook will be a vital resource for students of human resources management, business studies and public management policy, as well as for researchers with an interest in talent management, international management, and entrepreneurship and innovation.
810 kr
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2 099 kr
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468 kr
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Exploring and showcasing how global collaboration can foster entrepreneurship education, international contributors share their experiences as educators, scholars and thought-leaders involved in the Babson Collaborative. Chapters illustrate the challenges faced by educators and creative methods for tackling them, offering useful insights from a range of disciplinary perspectives. Highlighting the significance of the field to higher education environments, this book encourages active participation in entrepreneurial practice and collaboration between stakeholders and disciplines to ensure high-quality education in a variety of settings.
This insightful book is a rousing and inspiring view of entrepreneurship education for scholars and academic entrepreneurs who are working to build robust education ecosystems in the field.
527 kr
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1 297 kr
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1 672 kr
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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.
1 083 kr
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