This accessible book presents a coherent overview of non-Euclidean similarity learning, offering a range of perspectives on similarity-based pattern analysis and recognition methods from purely theoretical challenges to practical, real-world applications.
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This accessible book presents a coherent overview of non-Euclidean similarity learning, offering a range of perspectives on similarity-based pattern analysis and recognition methods from purely theoretical challenges to practical, real-world applications.
Read Less
