publications

2025

1. arXiv

   Missing Data in Signal Processing and Machine Learning: Models, Methods and Modern Approaches

   Alexandre Hippert-Ferrer, Aude Sportisse, Amirhossein Javaheri, Mohammed Nabil El Korso, and Daniel P. Palomar

   2025

   Bib

   @misc{hippertferrer2025missingdatasignalprocessing,
     title = {Missing Data in Signal Processing and Machine Learning: Models, Methods and Modern Approaches},
     author = {Hippert-Ferrer, Alexandre and Sportisse, Aude and Javaheri, Amirhossein and Korso, Mohammed Nabil El and Palomar, Daniel P.},
     year = {2025},
     eprint = {2506.01696},
     archiveprefix = {arXiv},
     primaryclass = {eess.SP},
     url = {https://arxiv.org/abs/2506.01696}
   }

2. EUSIPCO

   Clustering of Incomplete Data via a Bipartite Graph Structure

   Amirhossein Javaheri, and Daniel P. Palomar

   2025

   Bib

   @misc{javaheri2025clusteringincompletedatabipartite,
     title = {Clustering of Incomplete Data via a Bipartite Graph Structure},
     author = {Javaheri, Amirhossein and Palomar, Daniel P.},
     year = {2025},
     eprint = {2505.08594},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG},
     url = {https://arxiv.org/abs/2505.08594}
   }

3. TSP

   Time-Varying Graph Learning for Data With Heavy-Tailed Distribution

   Amirhossein Javaheri, Jiaxi Ying, Daniel P. Palomar, and Farokh Marvasti

   IEEE Transactions on Signal Processing, 2025

   DOI Bib

   @article{javaheri2024timevaryinggraphlearningdata,
     author = {Javaheri, Amirhossein and Ying, Jiaxi and Palomar, Daniel P. and Marvasti, Farokh},
     journal = {IEEE Transactions on Signal Processing},
     title = {Time-Varying Graph Learning for Data With Heavy-Tailed Distribution},
     year = {2025},
     volume = {73},
     number = {},
     pages = {3044-3060},
     keywords = {Data models;Laplace equations;Topology;Covariance matrices;Mathematical models;Heavily-tailed distribution;Vectors;Analytical models;Network topology;Graphical models;Time-varying;graph learning;Laplacian matrix;data clustering;heavy-tailed distribution;corrupted measurements;financial data},
     doi = {10.1109/TSP.2025.3588173}
   }

2024

1. EUSIPCO

   Learning Time-Varying Graphs for Heavy-Tailed Data Clustering

   Amirhossein Javaheri, and Daniel P. Palomar

   In 2024 32nd European Signal Processing Conference (EUSIPCO), 2024

   DOI Bib

   @inproceedings{10714943,
     author = {Javaheri, Amirhossein and Palomar, Daniel P.},
     booktitle = {2024 32nd European Signal Processing Conference (EUSIPCO)},
     title = {Learning Time-Varying Graphs for Heavy-Tailed Data Clustering},
     year = {2024},
     volume = {},
     number = {},
     pages = {2472-2476},
     keywords = {Learning systems;Heavily-tailed distribution;Estimation;Stochastic processes;Europe;Signal processing;Probabilistic logic;Data models;Numerical models;Topology;Time-varying;graph learning;data clustering;heavy-tailed distribution;financial data},
     doi = {10.23919/EUSIPCO63174.2024.10714943}
   }

2. ICASSP

   Joint Signal Recovery and Graph Learning from Incomplete Time-Series

   Amirhossein Javaheri, Arash Amini, Farokh Marvasti, and Daniel P. Palomar

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

   DOI Bib

   @inproceedings{10448021,
     author = {Javaheri, Amirhossein and Amini, Arash and Marvasti, Farokh and Palomar, Daniel P.},
     booktitle = {ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
     title = {Joint Signal Recovery and Graph Learning from Incomplete Time-Series},
     year = {2024},
     volume = {},
     number = {},
     pages = {13511-13515},
     keywords = {Minimization methods;Simulation;Computational modeling;Signal processing algorithms;Signal processing;Inference algorithms;Acoustics;Graph signal;graph learning;incomplete data;missing sample recovery;time-series},
     doi = {10.1109/ICASSP48485.2024.10448021}
   }

3. TSP

   Learning Spatiotemporal Graphical Models From Incomplete Observations

   Amirhossein Javaheri, Arash Amini, Farokh Marvasti, and Daniel P. Palomar

   IEEE Transactions on Signal Processing, 2024

   DOI Bib

   @article{10471585,
     author = {Javaheri, Amirhossein and Amini, Arash and Marvasti, Farokh and Palomar, Daniel P.},
     journal = {IEEE Transactions on Signal Processing},
     title = {Learning Spatiotemporal Graphical Models From Incomplete Observations},
     year = {2024},
     volume = {72},
     number = {},
     pages = {1361-1374},
     keywords = {Laplace equations;Graphical models;Reactive power;Mathematical models;Estimation;Directed graphs;Data models;Graph learning;graph signal recovery;incomplete data;Laplacian matrix;time-varying signal;vector auto regressive (VAR);Gaussian Markov random field (GMRF)},
     doi = {10.1109/TSP.2024.3354572}
   }

2023

1. CAMSAP

   Graph Learning for Balanced Clustering of Heavy-Tailed Data

   Amirhossein Javaheri, José Vinícius De M. Cardoso, and Daniel P. Palomar

   In 2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2023

   DOI Bib

   @inproceedings{10403460,
     author = {Javaheri, Amirhossein and De M. Cardoso, José Vinícius and Palomar, Daniel P.},
     booktitle = {2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},
     title = {Graph Learning for Balanced Clustering of Heavy-Tailed Data},
     year = {2023},
     volume = {},
     number = {},
     pages = {481-485},
     keywords = {Heavily-tailed distribution;Machine learning algorithms;Conferences;Machine learning;Size measurement;Data models;Computational efficiency;Graph learning;Laplacian matrix;data clustering;balancedness;heavy-tailed distribution;financial data},
     doi = {10.1109/CAMSAP58249.2023.10403460}
   }

2022

1. SPL

   Non-Coherent DOA Estimation via Majorization-Minimization Using Sign Information

   Mohamadreza Delbari, Amirhossein Javaheri, Hadi Zayyani, and Farrokh Marvasti

   IEEE Signal Processing Letters, 2022

   DOI Bib

   @article{9741322,
     author = {Delbari, Mohamadreza and Javaheri, Amirhossein and Zayyani, Hadi and Marvasti, Farrokh},
     journal = {IEEE Signal Processing Letters},
     title = {Non-Coherent DOA Estimation via Majorization-Minimization Using Sign Information},
     year = {2022},
     volume = {29},
     number = {},
     pages = {892-896},
     keywords = {Direction-of-arrival estimation;Estimation;Signal processing algorithms;Signal to noise ratio;Signal resolution;Simulation;Sensor arrays;DOA estimation;majorization-minimization;non-coherent;sign measurements;sparse recovery},
     doi = {10.1109/LSP.2022.3162153}
   }

2021

1. TCSEB

   A Robust Generalized Proportionate Diffusion LMS Algorithm for Distributed Estimation

   Hadi Zayyani, and Amirhossein Javaheri

   IEEE Transactions on Circuits and Systems II: Express Briefs, 2021

   DOI Bib

   @article{9219208,
     author = {Zayyani, Hadi and Javaheri, Amirhossein},
     journal = {IEEE Transactions on Circuits and Systems II: Express Briefs},
     title = {A Robust Generalized Proportionate Diffusion LMS Algorithm for Distributed Estimation},
     year = {2021},
     volume = {68},
     number = {4},
     pages = {1552-1556},
     keywords = {Cost function;Estimation;Signal processing algorithms;Indexes;Sensors;Circuits and systems;Robustness;Distributed estimation;proportionate;impulsive noise;robust;disturbance;diffusion LMS},
     doi = {10.1109/TCSII.2020.3029780}
   }

2018

1. SPL

   Robust Sparse Recovery in Impulsive Noise via Continuous Mixed Norm

   Amirhossein Javaheri, Hadi Zayyani, Mario A. T. Figueiredo, and Farrokh Marvasti

   IEEE Signal Processing Letters, 2018

   DOI Bib

   @article{8379452,
     author = {Javaheri, Amirhossein and Zayyani, Hadi and Figueiredo, Mario A. T. and Marvasti, Farrokh},
     journal = {IEEE Signal Processing Letters},
     title = {Robust Sparse Recovery in Impulsive Noise via Continuous Mixed Norm},
     year = {2018},
     volume = {25},
     number = {8},
     pages = {1146-1150},
     keywords = {Robustness;Signal processing algorithms;Noise measurement;Optimization;Minimization;Convergence;Noise robustness;Continuous mixed norm (CMN);impulsive noise;majorization–minimization (MM);robust sparse recovery;symmetric a-Stable (SaS) distribution},
     doi = {10.1109/LSP.2018.2846479}
   }

2. ESP

   Sparse recovery of missing image samples using a convex similarity index

   Amirhossein Javaheri, Hadi Zayyani, and Farokh Marvasti

   Signal Processing, 2018

   Abs DOI Bib

   This paper investigates the problem of recovering missing samples using methods based on sparse representation adapted for visually enhanced quality of reconstruction of image signals. Although, the popular Mean Square Error (MSE) criterion is convex and simple, it may not be entirely consistent with Human Visual System (HVS). Thus, instead of ℓ2-norm or MSE, a new perceptual quality measure is used as the similarity criterion between the original and the reconstructed images. The proposed criterion called Convex SIMilarity (CSIM) index is a modified version of the Structural SIMilarity (SSIM) index, which despite its predecessor, is convex and uni-modal. We derive mathematical properties for the proposed index and show how to optimally choose the parameters of the proposed criterion, investigating the Restricted Isometry (RIP) and error-sensitivity properties. We also propose an iterative sparse recovery method based on a constrained ℓ1-norm minimization problem, incorporating CSIM as the fidelity criterion. The resulting convex optimization problem is solved via an algorithm based on Alternating Direction Method of Multipliers (ADMM). Taking advantage of the convexity of the CSIM index, we also prove the convergence of the algorithm to the globally optimal solution of the proposed optimization problem, starting from any arbitrary point. Simulation results confirm the performance of the new similarity index as well as the proposed algorithm for missing sample recovery of image patch signals.

   @article{JAVAHERI201890,
     title = {Sparse recovery of missing image samples using a convex similarity index},
     journal = {Signal Processing},
     volume = {152},
     pages = {90-103},
     year = {2018},
     issn = {0165-1684},
     doi = {https://doi.org/10.1016/j.sigpro.2018.05.022},
     url = {https://www.sciencedirect.com/science/article/pii/S0165168418301919},
     author = {Javaheri, Amirhossein and Zayyani, Hadi and Marvasti, Farokh},
     keywords = {Missing sample recovery, Sparse approximation, Convex similarity index, RIP, ADMM, Image completion}
   }

2017

1. arXiv

   On Higher Order Positive Differential Energy Operator

   Amirhossein Javaheri, and Mohammad Bagher Shamsollahi

   2017

   Bib

   @misc{javaheri2017higherorderpositivedifferential,
     title = {On Higher Order Positive Differential Energy Operator},
     author = {Javaheri, Amirhossein and Shamsollahi, Mohammad Bagher},
     year = {2017},
     eprint = {1701.03834},
     archiveprefix = {arXiv},
     primaryclass = {cs.SD},
     url = {https://arxiv.org/abs/1701.03834}
   }