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  • Latent Factor Analysis for High-dimensional and Sparse Matrices

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    Series series Computer Science (R0)
    Latent factor analysis models are an effective type of machine learning model for addressing high-dimensional and sparse matrices, which are encountered in many big-data-related industrial applications. The performance of a latent factor analysis model relies heavily on appropriate hyper-parameters. However, most hyper-parameters are data-dependent, and using grid-search to tune these hyper ... Leer más

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    5th International Conference, IScIDE 2015, Suzhou, China, June 14-16, 2015, Revised Selected Papers, Part II

    Series Libro 2 - Springer Nature Proceedings Computer Science
    The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015.The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern ... Leer más

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  • Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013

    Series series Springer Nature Proceedings excluding Computer Science
    International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA) is one of the flagship conferences on Bio-Computing, bringing together the world’s leading scientists from different areas of Natural Computing. Since 2006, the conferences have taken place at Wuhan (2006), Zhengzhou (2007), Adelaide (2008), Beijing (2009), Liverpool & Changsha (2010), Malaysia (2011) and India ... Leer más

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  • Sparse Representation, Modeling and Learning in Visual Recognition

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  • Handbook of Robust Low-Rank and Sparse Matrix Decomposition

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  • Sparse Coding And Its Applications In Computer Vision

    This book provides a broader introduction to the theories and applications of sparse coding techniques in computer vision research. It introduces sparse coding in the context of representation learning, illustrates the fundamental concepts, and summarizes the most active research directions. A variety of applications of sparse coding are discussed, ranging from low-level image processing tasks ... Leer más

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  • Mathematical Problems in Data Science

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    This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods. For unsolved problems such as incomplete data relation and reconstruction, the book ... Leer más

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  • Blind Source Separation

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    A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studiesThe book presents an overview of Blind Source Separation, a relatively new signal processing method. Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on ... Leer más

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  • 5G for Future Wireless Networks

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    Series series Springer Nature Proceedings Computer Science
    This book constitutes the proceedings of the First International Conference on 5G for Future Wireless Networks, 5GWN 2017, held in Beijing, China, in April 2017. The 64 full papers were selected from 135 submissions and present the state of the art and practical applications of 5G technologies. The exponentially growing data traffic caused by the development of mobile Internet and smart phones ... Leer más

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    This book belongs to the subject of control and systems theory. It studies a novel data-driven framework for the design and analysis of iterative learning control (ILC) for nonlinear discrete-time systems. A series of iterative dynamic linearization methods is discussed firstly to build a linear data mapping with respect of the system’s output and input between two consecutive iterations. On this ... Leer más

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    A dynamic network is frequently encountered in various real industrial applications, such as the Internet of Things. It is composed of numerous nodes and large-scale dynamic real-time interactions among them, where each node indicates a specified entity, each directed link indicates a real-time interaction, and the strength of an interaction can be quantified as the weight of a link. As the ... Leer más

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    Third International Conference, ICCCS 2017, Nanjing, China, June 16-18, 2017, Revised Selected Papers, Part II

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    This two volume set LNCS 10602 and LNCS 10603 constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Cloud Computing and Security, ICCCS 2017, held in Nanjing, China, in June 2017.The 116 full papers and 11 short papers of these volumes were carefully reviewed and selected from 391 submissions. The papers are organized in topical sections such as: ... Leer más

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