Master's Thesis
Establishing lower complexity bounds for large-scale binary logistic regression using first-order methods.
Background and Description
This master's thesis is concerned with establishing a lower complexity bound for solving large-scale binary logistic regression problems via first-order methods.
Read the thesis
The full write-up and proofs for the complexity bound.
View the defense
Slide deck overview of the results and methodology.
Read the preprint
Early draft of the work prepared for publication.
AIMS IPI Journal
Peer-reviewed publication derived from the thesis.