44 citations · 153 across the 39 of their papers we have counts for
4 papers · 1 filter
Inexact Newton-type Methods for Optimisation with Nonnegativity Constraints
Oscar Smee, Fred Roosta
We consider solving large scale nonconvex optimisation problems with nonnegativity constraints. Such problems arise frequently in machine learning, such as nonnegative least-square…
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution
Eslam Zaher, Maciej Trzaskowski, Quan Nguyen +1
In this paper, we dive into the reliability concerns of Integrated Gradients (IG), a prevalent feature attribution method for black-box deep learning models. We particularly addres…
Bi-level Guided Diffusion Models for Zero-Shot Medical Imaging Inverse Problems
Hossein Askari, Fred Roosta, Hongfu Sun
In the realm of medical imaging, inverse problems aim to infer high-quality images from incomplete, noisy measurements, with the objective of minimizing expenses and risks to patie…
Conjugate Direction Methods Under Inconsistent Systems
Alexander Lim, Yang Liu, Fred Roosta
Since the development of the conjugate gradient (CG) method in 1952 by Hestenes and Stiefel, CG, has become an indispensable tool in computational mathematics for solving positive…