4 papers
Global Convergence of Adaptive Sensing for Principal Eigenvector Estimation
Alex Saad-Falcon, Brighton Ancelin, Justin Romberg
Principal component analysis classically requires full -dimensional samples, yet in various applications hardware limits acquisition to a few scalar measurements per sample. We…
MANGO: Learning Disentangled Image Transformation Manifolds with Grouped Operators
Brighton Ancelin, Yenho Chen, Peimeng Guan +4
Learning semantically meaningful image transformations (i.e. rotation, thickness, blur) directly from examples can be a challenging task. Recently, the Manifold Autoencoder (MAE) p…
Radon Implicit Field Transform (RIFT): Learning Scenes from Radar Signals
Daqian Bao, Alex Saad-Falcon, Justin Romberg
Data acquisition in array signal processing (ASP) is costly because achieving high angular and range resolutions necessitates large antenna apertures and wide frequency bandwidths,…
Rapid Grassmannian Averaging with Chebyshev Polynomials
Brighton Ancelin, Alex Saad-Falcon, Kason Ancelin +1
We propose new algorithms to efficiently average a collection of points on a Grassmannian manifold in both the centralized and decentralized settings. Grassmannian points are used…