Convex Quadratic Approximation. - J. Ben Rosen; Roummel F. Marcia (Comput. Optim. Appl., 2004)

Iterative Convex Quadratic Approximation for Global Optimization in Protein Docking. - Roummel F. Marcia; Julie C. Mitchell; J. Ben Rosen (Comput. Optim. Appl., 2005)

A pivoting strategy for symmetric tridiagonal matrices. - James R. Bunch; Roummel F. Marcia (Numer. Linear Algebra Appl., 2005)

A simplified pivoting strategy for symmetric tridiagonal matrices. - James R. Bunch; Roummel F. Marcia (Numer. Linear Algebra Appl., 2006)

Multi-funnel optimization using Gaussian underestimation. - Roummel F. Marcia; Julie C. Mitchell; J. Ben Rosen (J. Glob. Optim., 2007)

Global optimization in protein docking using clustering, underestimation and semidefinite programming. - Roummel F. Marcia; Julie C. Mitchell; Stephen J. Wright 001 (Optim. Methods Softw., 2007)

Compressive coded aperture video reconstruction. - Roummel F. Marcia; Rebecca M. Willett (EUSIPCO, 2008)

Compressive coded aperture superresolution image reconstruction. - Roummel F. Marcia; Rebecca Willett (ICASSP, 2008)

Fast disambiguation of superimposed images for increased field of view. - Roummel F. Marcia; Changsoon Kim; Jungsang Kim; David J. Brady; Rebecca Willett (ICIP, 2008)

Compressive coded aperture imaging. - Roummel F. Marcia; Zachary T. Harmany; Rebecca Willett (Computational Imaging, 2009)

Sequential probability assignment via online convex programming using exponential families. - Maxim Raginsky; Roummel F. Marcia; Jorge G. Silva; Rebecca M. Willett (ISIT, 2009)

Sequential anomaly detection in the presence of noise and limited feedback - Maxim Raginsky; Roummel F. Marcia; Jorge G. Silva; Rebecca Willett (CoRR, 2009)

SPIRAL out of convexity: sparsity-regularized algorithms for photon-limited imaging. - Zachary T. Harmany; Roummel F. Marcia; Rebecca Willett (Computational Imaging, 2010)

Gradient projection for linearly constrained convex optimization in sparse signal recovery. - Zachary T. Harmany; Daniel Thompson; Rebecca Willett; Roummel F. Marcia (ICIP, 2010)

Poisson image reconstruction with total variation regularization. - Rebecca Willett; Zachary T. Harmany; Roummel F. Marcia (ICIP, 2010)

Sparsity-regularized photon-limited imaging. - Zachary T. Harmany; Roummel F. Marcia; Rebecca Willett (ISBI, 2010)

Compressed sensing performance bounds under Poisson noise. - Maxim Raginsky; Rebecca Willett; Zachary T. Harmany; Roummel F. Marcia (IEEE Trans. Signal Process., 2010)

Bounded gradient projection methods for sparse signal recovery. - James Hernandez; Zachary T. Harmany; Daniel Thompson; Roummel F. Marcia (ICASSP, 2011)

Sparse video recovery using Linearly Constrained Gradient Projection. - Daniel Thompson; Zachary T. Harmany; Roummel F. Marcia (ICASSP, 2011)

A backward stability analysis of diagonal pivoting methods for solving unsymmetric tridiagonal systems without interchanges. - Jennifer B. Erway; Roummel F. Marcia (Numer. Linear Algebra Appl., 2011)

Performance Bounds for Expander-Based Compressed Sensing in Poisson Noise. - Maxim Raginsky; Sina Jafarpour; Zachary T. Harmany; Roummel F. Marcia; Rebecca M. Willett; A. Robert Calderbank (IEEE Trans. Signal Process., 2011)

Compressive video recovery with upper and lower bound constraints. - David R. Jones; Rachel O. Schlick; Roummel F. Marcia (ICASSP, 2012)

This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms - Theory and Practice. - Zachary T. Harmany; Roummel F. Marcia; Rebecca M. Willett (IEEE Trans. Image Process., 2012)

Sequential Anomaly Detection in the Presence of Noise and Limited Feedback. - Maxim Raginsky; Rebecca M. Willett; Corinne Horn; Jorge G. Silva; Roummel F. Marcia (IEEE Trans. Inf. Theory, 2012)

Shifted limited-memory DFP systems. - Jennifer B. Erway; Vibhor Jain; Roummel F. Marcia (ACSSC, 2013)

Dual-scale masks for spatio-temporal compressive imaging. - Zachary T. Harmany; Roummel F. Marcia; Rebecca M. Willett (GlobalSIP, 2013)

Compressive Coded Aperture Keyed Exposure Imaging with Optical Flow Reconstruction. - Zachary T. Harmany; Roummel F. Marcia; Rebecca M. Willett (CoRR, 2013)

Shifted L-BFGS systems. - Jennifer B. Erway; Vibhor Jain; Roummel F. Marcia (Optim. Methods Softw., 2014)

Algorithm 943: MSS: MATLAB Software for L-BFGS Trust-Region Subproblems for Large-Scale Optimization. - Jennifer B. Erway; Roummel F. Marcia (ACM Trans. Math. Softw., 2014)

p-th Power total variation regularization in photon-limited imaging via iterative reweighting. - Lasith Adhikari; Roummel F. Marcia (EUSIPCO, 2015)

Nonconvex relaxation for Poisson intensity reconstruction. - Lasith Adhikari; Roummel F. Marcia (ICASSP, 2015)

Nonconvex reconstruction for low-dimensional fluorescence molecular tomographic poisson observations. - Lasith Adhikari; Dianwen Zhu; Changqing Li; Roummel F. Marcia (ICIP, 2015)

On Efficiently Computing the Eigenvalues of Limited-Memory Quasi-Newton Matrices. - Jennifer B. Erway; Roummel F. Marcia (SIAM J. Matrix Anal. Appl., 2015)

Constrained variant detection with SPaRC: Sparsity, parental relatedness, and coverage. - Mario Banuelos; Rubi Almanza; Lasith Adhikari; Roummel F. Marcia; Suzanne Sindi (EMBC, 2016)

Sparse reconstruction for fluorescence lifetime imaging microscopy with poisson noise. - Lasith Adhikari; Arnold D. Kim; Roummel F. Marcia (GlobalSIP, 2016)

Sparse signal recovery methods for variant detection in next-generation sequencing data. - Mario Banuelos; Rubi Almanza; Lasith Adhikari; Suzanne Sindi; Roummel F. Marcia (ICASSP, 2016)

Analysis of p-norm regularized subproblem minimization for sparse photon-limited image recovery. - Aramayis Orkusyan; Lasith Adhikari; Joanna Valenzuela; Roummel F. Marcia (ICASSP, 2016)

Bounded sparse photon-limited image recovery. - Lasith Adhikari; Roummel F. Marcia (ICIP, 2016)

Nonconvex sparse poisson intensity reconstruction for time-dependent bioluminescence tomography. - Lasith Adhikari; Arnold D. Kim; Roummel F. Marcia (ISITA, 2016)

Trust-region methods for nonconvex sparse recovery optimization. - Jennifer B. Erway; Robert J. Plemmons; Lasith Adhikari; Roummel F. Marcia (ISITA, 2016)

Sparse genomic structural variant detection: Exploiting parent-child relatedness for signal recovery. - Mario Banuelos; Rubi Almanza; Lasith Adhikari; Roummel F. Marcia; Suzanne Sindi (SSP, 2016)

Group-sparse subspace clustering with missing data. - Daniel L. Pimentel-Alarcón; Laura Balzano; Roummel F. Marcia; Robert D. Nowak; Rebecca Willett (SSP, 2016)

Photon-Limited fluorescence lifetime imaging microscopy signal recovery with known bounds. - Omar DeGuchy; Lasith Adhikari; Arnold D. Kim; Roummel F. Marcia (CAMSAP, 2017)

Sparse diploid spatial biosignal recovery for genomic variation detection. - Mario Banuelos; Lasith Adhikari; Rubi Almanza; Andrew Fujikawa; Jonathan Sahagun; Katharine Sanderson; Melissa Spence; Suzanne Sindi; Roummel F. Marcia (MeMeA, 2017)

Nonconvex regularization for sparse genomic variant signal detection. - Mario Banuelos; Lasith Adhikari; Rubi Almanza; Andrew Fujikawa; Jonathan Sahagun; Katharine Sanderson; Melissa Spence; Suzanne Sindi; Roummel F. Marcia (MeMeA, 2017)

Nonconvex Regularization-Based Sparse Recovery and Demixing With Application to Color Image Inpainting. - Fei Wen; Lasith Adhikari; Ling Pei; Roummel F. Marcia; Peilin Liu; Robert C. Qiu (IEEE Access, 2017)

On solving L-SR1 trust-region subproblems. - Johannes Brust; Jennifer B. Erway; Roummel F. Marcia (Comput. Optim. Appl., 2017)

Detecting Novel Structural Variants In Genomes By Leveraging Parent-Child Relatedness. - Melissa Spence; Mario Banuelos; Roummel F. Marcia; Suzanne Sindi (BIBM, 2018)

Structural Variant Prediction in Extended Pedigrees Through Sparse Negative Binomial Genome Signal Recovery. - Mario Banuelos; Suzanne Sindi; Roummel F. Marcia (EMBC, 2018)

Trust-Region Minimization Algorithm for Training Responses (TRMinATR): The Rise of Machine Learning Techniques. - Jacob Rafati; Omar DeGuchy; Roummel F. Marcia (EUSIPCO, 2018)

Negative Binomial Optimization for Biomedical Structural Variant Signal Reconstruction. - Mario Banuelos; Suzanne Sindi; Roummel F. Marcia (ICASSP, 2018)

Improving L-BFGS Initialization for Trust-Region Methods in Deep Learning. - Jacob Rafati; Roummel F. Marcia (ICMLA, 2018)

Quasi-Newton Optimization in Deep Q-Learning for Playing ATARI Games. - Jacob Rafati; Roummel F. Marcia (CoRR, 2018)

Compact representation of the full Broyden class of quasi-Newton updates. - Omar DeGuchy; Jennifer B. Erway; Roummel F. Marcia (Numer. Linear Algebra Appl., 2018)

Fine Tuning Sparsity Penalties to Improve Structural Variant Detection. - Xiaolong Chen; Hansell Perez; Melissa Spence; Roummel F. Marcia; Suzanne Sindi (BIBM, 2019)

Deep Neural Networks for Low-resolution Photon-limited Imaging. - Omar DeGuchy; Fabian Santiago; Mario Banuelos; Roummel F. Marcia (ICASSP, 2019)

Predicting Novel and Inherited Variants in Parent-Child Trios. - Melissa Spence; Mario Banuelos; Roummel F. Marcia; Suzanne Sindi (MeMeA, 2019)

A dense initialization for limited-memory quasi-Newton methods. - Johannes Brust; Oleg Burdakov; Jennifer B. Erway; Roummel F. Marcia (Comput. Optim. Appl., 2019)

Large-scale quasi-Newton trust-region methods with low-dimensional linear equality constraints. - Johannes Brust; Roummel F. Marcia; Cosmin G. Petra (Comput. Optim. Appl., 2019)

Quasi-Newton Optimization Methods For Deep Learning Applications. - Jacob Rafati; Roummel F. Marcia (CoRR, 2019)

Detecting novel genomic structural variants through negative binomial optimization. - Andrew Lazar; Mario Banuelos; Suzanne Sindi; Roummel F. Marcia (ACSSC, 2020)

A Neural Network Approach for Anomaly Detection in Genomic Signals. - Erica Sawyer; Mario Banuelos; Roummel F. Marcia; Suzanne Sindi (APSIPA, 2020)

Related Inference: A Supervised Learning Approach to Detect Signal Variation in Genome Data. - Mario Banuelos; Omar DeGuchy; Suzanne Sindi; Roummel F. Marcia (EUSIPCO, 2020)

Genomic Signal Processing for Variant Detection in Diploid Parent-Child Trios. - Melissa Spence; Mario Banuelos; Roummel F. Marcia; Suzanne Sindi (EUSIPCO, 2020)

Image Classification in Synthetic Aperture Radar Using Reconstruction from Learned Inverse Scattering. - Jacqueline Alvarez; Omar DeGuchy; Roummel F. Marcia (IGARSS, 2020)

Deep Convolutional Autoencoders for Deblurring and Denoising Low-Resolution Images. - Michael Fernando Mendez Jimenez; Omar DeGuchy; Roummel F. Marcia (ISITA, 2020)

Trust-region algorithms for training responses: machine learning methods using indefinite Hessian approximations. - Jennifer B. Erway; Joshua D. Griffin; Roummel F. Marcia; Riadh Omheni (Optim. Methods Softw., 2020)

Computationally Efficient Decompositions of Oblique Projection Matrices. - Johannes Brust; Roummel F. Marcia; Cosmin G. Petra (SIAM J. Matrix Anal. Appl., 2020)

Convolution Padding in Recurrent Neural Networks for Image Denoising with Limited Data. - Alex Ho; Jacqueline Alvarez; Roummel F. Marcia (ACSCC, 2021)

Novel structural variant genome detection in extended pedigrees through negative binomial optimization. - Andrew Lazar; Mario Banuelos; Suzanne Sindi; Roummel F. Marcia (ACSCC, 2021)

Multi-Stage Gaussian Noise Reduction with Recurrent Neural Networks. - Aditya Ranganath; Omar DeGuchy; Mukesh Singhal; Roummel F. Marcia (ACSCC, 2021)

Data-Limited Deep Learning Methods for Mild Cognitive Impairment Classification in Alzheimer's Disease Patients. - Ashley De Luna; Roummel F. Marcia (EMBC, 2021)

Second-Order Trust-Region Optimization for Data-Limited Inference. - Aditya Ranganath; Omar DeGuchy; Mukesh Singhal; Roummel F. Marcia (EUSIPCO, 2021)

Machine Learning for Classifying Images with Motion Blur. - Rogelio E. Garcia; Jacqueline Alvarez; Roummel F. Marcia (ICMLA, 2022)

Interpretability of ReLU for Inversion. - Boaz Ilan; Aditya Ranganath; Jacqueline Alvarez; Shilpa Khatri; Roummel F. Marcia (ICMLA, 2022)

Recurrent Nerual Imaging: An Evolutionary Approach for Mixed Possion-Gaussian Image Denoising. - Aditya Ranganath; Omar DeGuchy; Fabian Santiago; Mukesh Singhal; Roummel F. Marcia (ICMLA, 2022)

Novel Adversarial Defense Techniques for White-Box Attacks. - Jason Van Tuinen; Aditya Ranganath; Goran Konjevod; Mukesh Singhal; Roummel F. Marcia (ICMLA, 2022)

Large-Scale Optimization with Linear Equality Constraints Using Reduced Compact Representation. - Johannes J. Brust; Roummel F. Marcia; Cosmin G. Petra; Michael A. Saunders (SIAM J. Sci. Comput., 2022)

Algorithm 1030: SC-SR1: MATLAB Software for Limited-memory SR1 Trust-region Methods. - Johannes Brust; Oleg Burdakov; Jennifer B. Erway; Roummel F. Marcia (ACM Trans. Math. Softw., 2022)

Sparse Overdispersed Photon-Limited Signal Recovery with Upper and Lower Bounds. - Yu Lu; Roummel F. Marcia (CAMSAP, 2023)

Overdispersed Photon-Limited Sparse Signal Recovery Using Nonconvex Regularization. - Yu Lu; Roummel F. Marcia (CAMSAP, 2023)

Decoding the Hidden: Direct Image Classification Using Coded Aperture Imaging. - Jocelyn Ornelas Munoz; Erica M. Rutter; Roummel F. Marcia (CAMSAP, 2023)

Parameterized Inverse Eigenvalue Problem for Quantum Sensing. - Kyle Wright; Roummel F. Marcia; Michael Scheibner; Boaz Ilan (CAMSAP, 2023)

Negative Binomial Optimization for Low-Count Overdispersed Sparse Signal Reconstruction. - Yu Lu; Roummel F. Marcia (EUSIPCO, 2023)

CLOT: Contrastive Learning-Driven and Optimal Transport-Based Training for Simultaneous Clustering. - Mohammed Aburidi; Roummel F. Marcia (ICIP, 2023)

Optimal Transport and Contrastive-Based Clustering for Annotation-Free Tissue Analysis in Histopathology Images. - Mohammed Aburidi; Roummel F. Marcia (ICMLA, 2023)

Genetic Variant Detection Over Generations: Sparsity-Constrained Optimization Using Block-Coordinate Descent. - Mohammed Aburidi; Mario Banuelos; Suzanne Sindi; Roummel F. Marcia (MeMeA, 2023)

Topological Adversarial Attacks on Graph Neural Networks Via Projected Meta Learning. - Mohammed Aburidi; Roummel F. Marcia (EAIS, 2024)

Optimal Transport-Based Network Alignment: Graph Classification of Small Molecule Structure-Activity Relationships in Biology. - Mohammed Aburidi; Roummel F. Marcia (EMBC, 2024)

Sparse Negative Binomial Signal Recovery for Genomic Variant Prediction in Diploid Species. - Jocelyn Ornelas Munoz; Erica M. Rutter; Mario Banuelos; Suzanne S. Sindi; Roummel F. Marcia (EMBC, 2024)

Contrastive Pre-Training and Multiple Instance Learning for Predicting Tumor Microsatellite Instability. - Ronald Nap; Mohammed Aburidi; Roummel F. Marcia (EMBC, 2024)

Alternating Direction Method of Multipliers for Negative Binomial Model with the Weighted Difference of Anisotropic and Isotropic Total Variation. - Yu Lu; Kevin Bui; Roummel F. Marcia (ICME, 2024)

Quasi-Adam: Accelerating Adam Using Quasi-Newton Approximations. - Aditya Ranganath; Irabiel Romero Ruiz; Mukesh Singhal; Roummel F. Marcia (ICMLA, 2024)

Sparse Signal Reconstruction for Overdispersed Low-Photon Count Biomedical Imaging Using ℓp Total Variation. - Yu Lu; Roummel F. Marcia (ISBI, 2024)

Negative Binomial Matrix Completion. - Yu Lu; Kevin Bui; Roummel F. Marcia (MLSP, 2024)

Wasserstein-Based Similarity Constrained Matrix Factorization for Drug-Drug Interaction Prediction. - Sarah Malone; Mohammed Aburidi; Roummel F. Marcia (SiPS, 2024)

Sparse Signal Reconstruction for Overdispersed Low-photon Count Biomedical Imaging Using ℓ Total Variation. - Yu Lu; Roummel F. Marcia (CoRR, 2024)

Shape-changing trust-region methods using multipoint symmetric secant matrices. - Johannes J. Brust; Jennifer B. Erway; Roummel F. Marcia (Optim. Methods Softw., 2024)

Signal Reconstructions for ECG-Transmembrane Voltage Potentials Using Transformers. - Jocelyn Ornelas Munoz; Gbocho M. Terasaki; Aditya Ranganath; Omar DeGuchy; Roummel F. Marcia (ISBI, 2025)

Noise Model Statistics Regularization for Deep Learning Biomedical Imaging. - Yu Lu; Roummel F. Marcia (MeMeA, 2025)

Inverse Eigenvalue Difference Problems for Quantum Dots. - Boaz Ilan; Roummel F. Marcia; Michael Scheibner; Kyle Wright (Numer. Linear Algebra Appl., 2025)

Symmetric Rank-One Quasi-Newton Methods for Deep Learning Using Cubic Regularization. - Aditya Ranganath; Mukesh Singhal; Roummel F. Marcia (CoRR, 2025)

Effective Dimension Aware Fractional-Order Stochastic Gradient Descent for Convex Optimization Problems. - Mohammad Partohaghighi; Roummel F. Marcia; YangQuan Chen (CoRR, 2025)

More Optimal Fractional-Order Stochastic Gradient Descent for Non-Convex Optimization Problems. - Mohammad Partohaghighi; Roummel F. Marcia; YangQuan Chen (CoRR, 2025)