19 citations · 25 across the 5 of their papers we have counts for
5 papers
Dynamic Subspace Estimation with Grassmannian Geodesics
Cameron J. Blocker, Haroon Raja, Jeffrey A. Fessler +1
Dynamic subspace estimation, or subspace tracking, is a fundamental problem in statistical signal processing and machine learning. This paper considers a geodesic model for time-va…
Adaptive Sampling for Linear Sensing Systems via Langevin Dynamics
Guanhua Wang, Douglas C. Noll, Jeffrey A. Fessler
Adaptive or dynamic signal sampling in sensing systems can adapt subsequent sampling strategies based on acquired signals, thereby potentially improving image quality and speed. Th…
HeMPPCAT: Mixtures of Probabilistic Principal Component Analysers for Data with Heteroscedastic Noise
Alec S. Xu, Laura Balzano, Jeffrey A. Fessler
Mixtures of probabilistic principal component analysis (MPPCA) is a well-known mixture model extension of principal component analysis (PCA). Similar to PCA, MPPCA assumes the data…
Training End-to-End Unrolled Iterative Neural Networks for SPECT Image Reconstruction
Zongyu Li, Yuni K. Dewaraja, Jeffrey A. Fessler
Training end-to-end unrolled iterative neural networks for SPECT image reconstruction requires a memory-efficient forward-backward projector for efficient backpropagation. This pap…
Fast dual proximal gradient algorithms with rate for convex minimization
Donghwan Kim, Jeffrey A. Fessler
We consider minimizing the composite function that consists of a strongly convex function and a convex function. The fast dual proximal gradient (FDPG) method decreases the dual fu…