Abhishek S. B.

2026

1. ICASSP 26

   Sparse recovery using tight frames and minimax concave penalty

   K. K. R. Nareddy, A. S. Bhandiwad, A. J. Kamath, and C. S. Seelamantula

   In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026

   Abs DOI

   Sparse signal recovery is an important problem in compressed sensing, signal/image processing, computational imaging and machine learning. The design of the sensing matrix is crucial in compressed sensing. While random Gaussian sensing matrices are relatively easier to construct, it is known that matrices constituting a tight frame provide superior reconstruction performance. We formulate the problem of sparse signal recovery using a new data-fidelity term that effectively "tightens" the sensing matrix, and incorporate the minimax concave penalty (MCP) instead of the ℓ1-norm for promoting sparsity. We carry out the optimization using a proximal gradient method and its Nesterov accelerated counterpart. Simulation results demonstrate that the proposed algorithms result in up to three times faster convergence and superior reconstruction accuracy over benchmark methods.

2025

1. ISCS 25

   Weakly-Convex Regularization for Magnetic Resonance Image Denoising

   A. Prabakar, A. S. Bhandiwad, A. J. Kamath, and C. S. Seelamantula

   2025

   BIB URL

   @misc{prabakar2025weakly,
     archiveprefix = {arXiv},
     author = {Prabakar, A. and Bhandiwad, A. S. and Kamath, A. J. and Seelamantula, C. S.},
     eprint = {2508.14438},
     primaryclass = {eess.SP},
     title = {Weakly-Convex Regularization for Magnetic Resonance Image Denoising},
     url = {https://arxiv.org/abs/2508.14438},
     year = {2025}
   }

2. ICASSP 25

   On the Design of Weakly-Convex Regularizers for Solving Linear Inverse Problems

   A. J. Kamath, A. S. Bhandiwad, and C. S. Seelamantula

   In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025

   BIB URL

   @inproceedings{kamath2025design,
     author = {Kamath, A. J. and Bhandiwad, A. S. and Seelamantula, C. S.},
     booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
     title = {On the Design of Weakly-Convex Regularizers for Solving Linear Inverse Problems},
     url = {https://scholar.google.com/citations?view_op=view_citation&hl=en&user=1g1i1B4AAAAJ&cstart=200&pagesize=100&citation_for_view=1g1i1B4AAAAJ:artPoR2Yc-kC},
     year = {2025}
   }

2024

1. ICASSP 24

   Variational Analysis of Adversarial Regularization for Solving Inverse Problems

   A. S. Bhandiwad, A. J. Kamath, S. Asokan, and C. S. Seelamantula

   In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024

   BIB URL

   @inproceedings{bhandiwad2024variational,
     author = {Bhandiwad, A. S. and Kamath, A. J. and Asokan, S. and Seelamantula, C. S.},
     booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
     title = {Variational Analysis of Adversarial Regularization for Solving Inverse Problems},
     url = {https://scholar.google.com/citations?view_op=view_citation&hl=en&user=1g1i1B4AAAAJ&cstart=100&pagesize=100&citation_for_view=1g1i1B4AAAAJ:GFxP56DSvIMC},
     year = {2024}
   }