Courtney Paquette

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Associate Academic Member
Courtney Paquette
Assistant Professor, Professeure adjointe, McGill University, Google
Courtney Paquette

Courtney Paquette is currently working as a Research Scientist at Google Brain, Montreal. Starting 2020, she will be joining the Mathematics and Statistics department at McGill University as an assistant professor.

Courtney received her Ph.D. from the Mathematics department at the University of Washington (2017) under Prof. Dmitriy Drusvyatskiy then she held a postdoctoral position in the Industrial and Systems Engineering at Lehigh University where she worked with Prof. Katya Scheinberg. She held an NSF postdoctoral fellowship (2018-2019) under Prof. Stephen Vavasis in the Combinatorics and Optimization Department at the University of Waterloo.

Her research broadly focuses on designing and analyzing algorithms for large-scale optimization problems, motivated by applications in data science.

Publications

2021-07

SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality
Courtney Paquette, Kiwon Lee, Fabian Pedregosa and Elliot Paquette

2021-06

Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models.
Courtney Paquette and Elliot Paquette
arXiv preprint arXiv:2106.03696
(2021-06-07)
ui.adsabs.harvard.eduPDF

2020-10

The nonsmooth landscape of phase retrieval
Damek Davis, Dmitriy Drusvyatskiy and Courtney Paquette
Ima Journal of Numerical Analysis
(2020-10-16)
academic.oup.comPDF

Publications collected and formatted using Paperoni

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