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Stefanie Jegelka
Associate Professor
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My research is in algorithmic machine learning, and spans modeling, optimization algorithms, theory and applications. In particular, we have been working on exploiting mathematical structure for discrete and combinatorial machine learning problems, for robustness and for scaling machine learning algorithms.
Papers130 papers
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ICLR 2021, (2021)
international conference on machine learning, (2020)
Edward Kim, Zach Jensen, Alexander van Grootel,Kevin Huang, Matthew Staib, Sheshera Mysore,Haw-Shiuan Chang,Emma Strubell,Andrew McCallum,Stefanie Jegelka,Elsa Olivetti
JOURNAL OF CHEMICAL INFORMATION AND MODELING, no. 3 (2020): 1194-1201
ICLR, (2020)
NIPS 2020, (2020)
ICML, pp.1984-1994, (2020)
ICML, pp.8127-8136, (2020)
ICML, pp.3419-3430, (2020)
international conference on learning representations, (2020)
international conference on learning representations, (2020)
NIPS 2020, (2020)
AISTATS, pp.2174-2184, (2020)
NIPS 2020, (2020)
NIPS 2020, (2020)
ICML, pp.11173-11182, (2020)
Meeting of the Association for Computational Linguistics, (2019)
ACL (1), pp.3180-3189, (2019)
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