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John Stewart Shawe-Taylor (born 1953) is Director of the Centre for Computational Statistics and Machine Learning at University College, London (UK). His main research area is statistical learning theory. He has contributed to a number of fields ranging from graph theory through cryptography to statistical learning theory and its applications. However, his main contributions have been in the development of the analysis and subsequent algorithmic definition of principled machine learning algorithms founded in statistical learning theory. This work has helped to drive a fundamental rebirth in the field of machine learning with the introduction of kernel methods and support vector machines, including the mapping of these approaches onto novel domains including work in computer vision, documen

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  • John Shawe-Taylor (en)
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  • John Stewart Shawe-Taylor (born 1953) is Director of the Centre for Computational Statistics and Machine Learning at University College, London (UK). His main research area is statistical learning theory. He has contributed to a number of fields ranging from graph theory through cryptography to statistical learning theory and its applications. However, his main contributions have been in the development of the analysis and subsequent algorithmic definition of principled machine learning algorithms founded in statistical learning theory. This work has helped to drive a fundamental rebirth in the field of machine learning with the introduction of kernel methods and support vector machines, including the mapping of these approaches onto novel domains including work in computer vision, documen (en)
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  • John Shawe-Taylor (en)
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  • John Shawe-Taylor (en)
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  • Regularity and Transitivity in Graphs (en)
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