1 citations · 1 across the 4 of their papers we have counts for
5 papers
Behavior Score Prediction in Resting-State Functional MRI by Deep State Space Modeling
Javier Salazar Cavazos, Maximillian Egan, Krisanne Litinas +2
Early clinical assessment of Alzheimer's disease relies on behavior scores that measure a subject's language, memory, and cognitive skills. On the medical imaging side, functional…
Alzheimers Disease Classification in Functional MRI With 4D Joint Temporal-Spatial Kernels in Novel 4D CNN Model
Javier Salazar Cavazos, Scott Peltier
Previous works in the literature apply 3D spatial-only models on 4D functional MRI data leading to possible sub-par feature extraction to be used for downstream tasks like classifi…
ALPCAHUS: Subspace Clustering for Heteroscedastic Data
Javier Salazar Cavazos, Jeffrey A Fessler, Laura Balzano
Principal component analysis (PCA) is a key tool in the field of data dimensionality reduction. Various methods have been proposed to extend PCA to the union of subspace (UoS) sett…
Smooth optimization using global and local low-rank regularizers
Rodrigo A. Lobos, Javier Salazar Cavazos, Raj Rao Nadakuditi +1
Many inverse problems and signal processing problems involve low-rank regularizers based on the nuclear norm. Commonly, proximal gradient methods (PGM) are adopted to solve this ty…
ALPCAH: Sample-wise Heteroscedastic PCA with Tail Singular Value Regularization
Javier Salazar Cavazos, Jeffrey A. Fessler, Laura Balzano
Principal component analysis (PCA) is a key tool in the field of data dimensionality reduction that is useful for various data science problems. However, many applications involve…