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Author Information
Jason Eisner (Johns Hopkins University)
Jason Eisner is Professor of Computer Science at Johns Hopkins University, as well as Director of Research at Microsoft Semantic Machines. He is a Fellow of the Association for Computational Linguistics. At Johns Hopkins, he is also affiliated with the Center for Language and Speech Processing, the Machine Learning Group, the Cognitive Science Department, and the national Center of Excellence in Human Language Technology. His goal is to develop the probabilistic modeling, inference, and learning techniques needed for a unified model of all kinds of linguistic structure. His 135+ papers have presented various algorithms for parsing, machine translation, and weighted finite-state machines; formalizations, algorithms, theorems, and empirical results in computational phonology; and unsupervised or semi-supervised learning methods for syntax, morphology, and word-sense disambiguation. He is also the lead designer of Dyna, a new declarative programming language that provides an infrastructure for AI research. He has received two school-wide awards for excellence in teaching, as well as recent Best Paper Awards at ACL 2017 and EMNLP 2019.
More from the Same Authors
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2020 Poster: Noise-Contrastive Estimation for Multivariate Point Processes »
Hongyuan Mei · Tom Wan · Jason Eisner -
2019 : Panel Discussion »
Jacob Andreas · Edward Gibson · Stefan Lee · Noga Zaslavsky · Jason Eisner · Jürgen Schmidhuber -
2018 : Panel Discussion »
Rich Caruana · Mike Schuster · Ralf Schlüter · Hynek Hermansky · Renato De Mori · Samy Bengio · Michiel Bacchiani · Jason Eisner -
2018 : Jason Eisner, "BiLSTM-FSTs and Neural FSTs" »
Jason Eisner -
2017 Poster: The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process »
Hongyuan Mei · Jason Eisner -
2014 Poster: Learning to Search in Branch and Bound Algorithms »
He He · Hal Daumé III · Jason Eisner -
2012 Poster: Imitation Learning by Coaching »
He He · Hal Daumé III · Jason Eisner -
2012 Poster: Learned Prioritization for Trading Off Accuracy and Speed »
Jiarong Jiang · Adam Teichert · Hal Daumé III · Jason Eisner