44 citations · 153 across the 39 of their papers we have counts for
6 papers · 1 filter
SALSA: Sequential Approximate Leverage-Score Algorithm with Application in Analyzing Big Time Series Data
Ali Eshragh, Luke Yerbury, Asef Nazari +2
We develop a new efficient sequential approximate leverage score algorithm, SALSA, using methods from randomized numerical linear algebra (RandNLA) for large matrices. We demonstra…
Non-Uniform Smoothness for Gradient Descent
Albert S. Berahas, Lindon Roberts, Fred Roosta
The analysis of gradient descent-type methods typically relies on the Lipschitz continuity of the objective gradient. This generally requires an expensive hyperparameter tuning pro…
A PAC-Bayesian Perspective on the Interpolating Information Criterion
Liam Hodgkinson, Chris van der Heide, Robert Salomone +2
Deep learning is renowned for its theory-practice gap, whereby principled theory typically fails to provide much beneficial guidance for implementation in practice. This has been h…
Obtaining Pseudo-inverse Solutions With MINRES
Yang Liu, Andre Milzarek, Fred Roosta
The celebrated minimum residual method (MINRES), proposed in the seminal paper of Paige and Saunders, has seen great success and widespread use in solving Hermitian (and complex-sy…
Complexity Guarantees for Nonconvex Newton-MR Under Inexact Hessian Information
Alexander Lim, Fred Roosta
We consider an extension of the Newton-MR algorithm for nonconvex unconstrained optimization to the settings where Hessian information is approximated. Under a particular noise mod…
The Interpolating Information Criterion for Overparameterized Models
Liam Hodgkinson, Chris van der Heide, Robert Salomone +2
The problem of model selection is considered for the setting of interpolating estimators, where the number of model parameters exceeds the size of the dataset. Classical informatio…