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John Lafferty is a leading expert in machine learning, language processing, and neuroscience applications. He is the John C. Malone Professor of Statistics and Data Science at Yale, with a secondary appointment in Computer Science, and the author of several best-selling books and papers.
John D. Lafferty is an American scientist, Professor at Yale University and leading researcher in machine learning. He is best known for proposing the Conditional Random Fields with Andrew McCallum and Fernando C.N. Pereira.
The Yale Statistical Machine Learning Group carries out research and training in machine learning with an emphasis on statistical analysis and principles. The group is directed by Prof. John Lafferty in the Department of Statistics and Data Science within the Faculty of Arts and Sciences at Yale.
Department of Statistics & Science Yale University 24 Hillhouse Avenue New Haven, CT 06511 Phone: 203-432-5216 Email: john.lafferty@yale.edu. Education. 1982–1986, Princeton University Ph.D. in Mathematics, 1986, M.A. in Mathematics, 1984 Member of the Program in Applied and Computational Mathematics Thesis advisor: Edward Nelson.
John Lafferty is a faculty member and associate director of the Center for Neurocomputation and Machine Intelligence at the Wu Tsai Institute for Neuroscience and Engineering at Yale University. He is a professor of statistics and data science, with a secondary appointment in computer science, and his research focuses on using machine learning to study the human brain and its functions.
John Lafferty. Yale University. No verified email. Machine Learning. Articles Cited by Public access. Title. Sort. Sort by citations Sort by year Sort by title. Cited by. Cited by. ... S Della Pietra, V Della Pietra, J Lafferty. IEEE transactions on pattern analysis and machine intelligence 19 (4), 380-393, 1997. 1691: 1997:
John C. Malone Professor of Statistics & Data Science. Kline Tower, Room 1221, 219 Prospect Street, New Haven, CT 06511. john.lafferty@yale.edu. Phone: +1 (203) 432-5216. Website. Department of Statistics and Data Science.
