82 citations · 241 across the 20 of their papers we have counts for
24 papers
Physics-Informed Koopman Network
Yuying Liu, Aleksei Sholokhov, Hassan Mansour +1
Koopman operator theory is receiving increased attention due to its promise to linearize nonlinear dynamics. Neural networks that are developed to represent Koopman operators have…
High-Contrast Reflection Tomography with Total-Variation Constraints
Ajinkya Kadu, Hassan Mansour, Petros T. Boufounos
Inverse scattering is the process of estimating the spatial distribution of the scattering potential of an object by measuring the scattered wavefields around it. In this paper, we…
On the modes of convergence of Stochastic Optimistic Mirror Descent (OMD) for saddle point problems
Yanting Ma, Shuchin Aeron, Hassan Mansour
In this article, we study the convergence of Mirror Descent (MD) and Optimistic Mirror Descent (OMD) for saddle point problems satisfying the notion of coherence as proposed in Mer…
CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
Jiawei Ma, Zheng Shou, Alireza Zareian +3
Many real-world applications involve multivariate, geo-tagged time series data: at each location, multiple sensors record corresponding measurements. For example, air quality monit…
Recovery Analysis of Damped Spectrally Sparse Signals and Its Relation to MUSIC
Shuang Li, Hassan Mansour, Michael B. Wakin
One of the classical approaches for estimating the frequencies and damping factors in a spectrally sparse signal is the MUSIC algorithm, which exploits the low-rank structure of an…
Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging
Hassan Mansour, Dehong Liu, Ulugbek S. Kamilov +1
A common problem that arises in radar imaging systems, especially those mounted on mobile platforms, is antenna position ambiguity. Approaches to resolve this ambiguity and correct…
Online Detection of Action Start in Untrimmed, Streaming Videos
Zheng Shou, Junting Pan, Jonathan Chan +5
We aim to tackle a novel task in action detection - Online Detection of Action Start (ODAS) in untrimmed, streaming videos. The goal of ODAS is to detect the start of an action ins…
A Short Note on Improved ROSETA
Hassan Mansour
This note presents a more efficient formulation of the robust online subspace estimation and tracking algorithm (ROSETA) that is capable of identifying and tracking a time-varying…
Accelerated Image Reconstruction for Nonlinear Diffractive Imaging
Yanting Ma, Hassan Mansour, Dehong Liu +2
The problem of reconstructing an object from the measurements of the light it scatters is common in numerous imaging applications. While the most popular formulations of the proble…
SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering
Hsiou-Yuan Liu, Dehong Liu, Hassan Mansour +3
Multiple scattering of an electromagnetic wave as it passes through an object is a fundamental problem that limits the performance of current imaging systems. In this paper, we des…
Guided Signal Reconstruction Theory
Andrew Knyazev, Akshay Gadde, Hassan Mansour +1
An axiomatic approach to signal reconstruction is formulated, involving a sample consistent set and a guiding set, describing desired reconstructions. New frame-less reconstruction…
Compressive Imaging with Iterative Forward Models
Hsiou-Yuan Liu, Ulugbek S. Kamilov, Dehong Liu +2
We propose a new compressive imaging method for reconstructing 2D or 3D objects from their scattered wave-field measurements. Our method relies on a novel, nonlinear measurement mo…
A Recursive Born Approach to Nonlinear Inverse Scattering
Ulugbek S. Kamilov, Dehong Liu, Hassan Mansour +1
The Iterative Born Approximation (IBA) is a well-known method for describing waves scattered by semi-transparent objects. In this paper, we present a novel nonlinear inverse scatte…
Representation and Coding of Signal Geometry
Petros T Boufounos, Shantanu Rane, Hassan Mansour
Approaches to signal representation and coding theory have traditionally focused on how to best represent signals using parsimonious representations that incur the lowest possible…
Learning optimal nonlinearities for iterative thresholding algorithms
Ulugbek S. Kamilov, Hassan Mansour
Iterative shrinkage/thresholding algorithm (ISTA) is a well-studied method for finding sparse solutions to ill-posed inverse problems. In this letter, we present a data-driven sche…
Guided Signal Reconstruction with Application to Image Magnification
Akshay Gadde, Andrew Knyazev, Dong Tian +1
We study the problem of reconstructing a signal from its projection on a subspace. The proposed signal reconstruction algorithms utilize a guiding subspace that represents desired…
Chebyshev and Conjugate Gradient Filters for Graph Image Denoising
Dong Tian, Hassan Mansour, Andrew Knyazev +1
In 3D image/video acquisition, different views are often captured with varying noise levels across the views. In this paper, we propose a graph-based image enhancement technique th…
Recovery Analysis for Weighted -Minimization Using a Null Space Property
Hassan Mansour, Rayan Saab
We study the recovery of sparse signals from underdetermined linear measurements when a potentially erroneous support estimate is available. Our results are twofold. First, we deri…
Non-Convex Compressed Sensing Using Partial Support Information
Navid Ghadermarzy, Hassan Mansour, Ozgur Yilmaz
In this paper we address the recovery conditions of weighted minimization for signal reconstruction from compressed sensing measurements when partial support information i…
A fast randomized Kaczmarz algorithm for sparse solutions of consistent linear systems
Hassan Mansour, Ozgur Yilmaz
The Kaczmarz algorithm is a popular solver for overdetermined linear systems due to its simplicity and speed. In this paper, we propose a modification that speeds up the convergenc…
Fast methods for denoising matrix completion formulations, with applications to robust seismic data interpolation
Aleksandr Y. Aravkin, Rajiv Kumar, Hassan Mansour +2
Recent SVD-free matrix factorization formulations have enabled rank minimization for systems with millions of rows and columns, paving the way for matrix completion in extremely la…
Beyond -norm minimization for sparse signal recovery
Hassan Mansour
Sparse signal recovery has been dominated by the basis pursuit denoise (BPDN) problem formulation for over a decade. In this paper, we propose an algorithm that outperforms BPDN in…
Support driven reweighted minimization
Hassan Mansour, Ozgur Yilmaz
In this paper, we propose a support driven reweighted minimization algorithm (SDRL1) that solves a sequence of weighted problems and relies on the support estimat…
Recovering Compressively Sampled Signals Using Partial Support Information
Michael P. Friedlander, Hassan Mansour, Rayan Saab +1
In this paper we study recovery conditions of weighted minimization for signal reconstruction from compressed sensing measurements when partial support information is avai…