About
I am a fifth year Ph.D. student in Computer Science at Stanford University co-advised by Gregory Valiant and John Duchi. My interests are in the intersection of algorithms, statistics, optimization, and machine learning. Before Stanford, I worked with John Lafferty at the University of Chicago. Prior to that, I received an MPhil in Scientific Computing at the University of Cambridge on a Churchill Scholarship where I was advised by Sergio Bacallado. I received a B.S. in Mathematics and B.A. in Chemistry at the University of Chicago.
Summer 2022: I am currently a research scientist intern at DeepMind in London.
Publications and Preprints
Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Efficient Convex Optimization Requires Superlinear Memory. COLT, 2022. Best Paper Award.
arXiv | conference pdf (alphabetical authorship)
Jonathan Kelner, Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Honglin Yuan, Big-Step-Little-Step: Gradient Methods for Objectives with Multiple Scales. COLT, 2022.
arXiv | code | conference pdf (alphabetical authorship)
Annie Marsden, John Duchi and Gregory Valiant, Misspecification in Prediction Problems and Robustness via Improper Learning. AISTATS, 2021. Selected for oral presentation.
arXiv | conference pdf
Annie Marsden, Sergio Bacallado. Sequential Matrix Completion. 2017. (arXiv pre-print)
arXiv | pdf
Annie Marsden, R. Stephen Berry. Enrichment of Network Diagrams for Potential Surfaces. The Journal of Physical Chemsitry, 2015.
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Annie Marsden. Eigenvalues of the laplacian and their relationship to the connectedness of a graph. 2013.
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Theses and Reports
Fourier Transformation at a Representation, Annie Marsden. Etude for the Park City Math Institute Undergraduate Summer School. July 2015.
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Szemerédi Regularity Lemma and Arthimetic Progressions, Annie Marsden. Done under the mentorship of M. Malliaris.
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Sequential Matrix Completion. Annie Marsden. University of Cambridge MPhil. Thesis, 2016.
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Teaching
Navajo Math Circles Instructor. 2019 (and hopefully 2022 onwards Covid permitting) For more information please watch this and please consider donating here!
Winter 2020 Teaching assistant for EE364a: Convex Optimization I taught by John Duchi
Fall 2018 Teaching assitant for CS265/CME309: Randomized Algorithms and Probabilistic Analysis, Fall 2019 taught by Greg Valiant