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Theory, Vol. 64, No. 3, March 2018. ESP: A Machine Learning Approach to Predicting Application Interference Nikita Mishra, John Lafferty, and Henry Hoffmann Proceedings of International Conference on Autonomic Computing, 2017. Testing for global network structure using small subgraph statistics Chao Gao and John Lafferty arXiv:1710.00862.
John Lafferty, PhD Princeton University. John C. Malone Professor of Statistics and Data Science. Address: 24 Hillhouse Avenue, Department of Statistics and Data Science. john.lafferty@yale.edu.
Selected Publications: Selective inference for group-sparse linear models, Advances in Neural Information Processing Systems 29, 2016. Fan Yang, Rina Foygel Barber, Prateek Jain, and John Lafferty, arxiv:1607.08211 Local minimax complexity of stochastic convex optimization, Yuancheng Zhu, Sabyasachi Chatterjee, John Duchi and John Lafferty.
John Lafferty. Department of Statistics and Data Science, Yale University. December 2019 NIPS'19: Proceedings of the 33rd International Conference on Neural Information Processing Systems. research-article. free. TopicEq: a joint topic and mathematical equation model for scientific texts. Michihiro Yasunaga.
35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics. pdf bib. Text Segmentation Using Exponential Models. Doug Beeferman | Adam Berger | John Lafferty. Second Conference on Empirical Methods in Natural Language Processing.
John Lafferty is the John C. Malone Professor of Statistics and Data Science at Yale, with a secondary appointment in Computer Science. Before joining Yale, Lafferty was Louis Block Professor in the Department of Statistics and the Department of Computer Science at the University of Chicago, and also Adjunct Professor at the Toyota Technological Institute of Chicago.
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