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In this excellent book, the editors deal with the state-of-the-art, current best practices, and some innovative applications of nearest-neighbor methods in learning and vision. This volume brings together contributions of top-level researchers in theory of computation, machine learning, and computer vision with the goal of closing up the gaps between disciplines and current state-of-the-art methods for emerging applications. All the content is well-written, highly relevant, original, and timely. The audience for this book consists of researchers, scientists, engineers, professionals, and academics, working not only in this field, but also in any field that could benefit from these powerful methods. This book can be particularly useful to researchers working on the basis set expansion networks.
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Francesco Gianfelici (2008) studied this question.
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