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Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the data well. The u... More

The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can easil... More

This volume presents selections of Peter J. Bickel's major papers, along with comments on their novelty and impact on the subsequent development of statistics as a discipline. Each of the eight parts concerns a particular area of research and provides new commentary by experts in the area. The parts... More

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 researc... More

This book not only introduces the principles of INS, CNS and GNSS, the related filters and semi-physical simulation, but also systematically discusses the key technologies needed for integrated navigations of INS/GNSS, INS/CNS, and INS/CNS/GNSS, respectively. INS/CNS/GNSS integrated navigation tech... More

This book constitutes the proceedings of the Third Workshop on Face and Facial Expression Recognition from Real World Videos, FFER 2018, and the Second International Workshop on Deep Learning for Pattern Recognition, DLPR 2018, held at the 24th International Conference on Pattern Recognition, ICPR 2... More