Saeed Razavikia

Orcid: 0000-0003-4519-9204

According to our database1, Saeed Razavikia authored at least 16 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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On csauthors.net:

Bibliography

2024
Harmonic retrieval using weighted lifted-structure low-rank matrix completion.
Signal Process., March, 2024

ChannelComp: A General Method for Computation by Communications.
IEEE Trans. Commun., 2024

Timely and Painless Breakups: Off-the-grid Blind Message Recovery and Users' Demixing.
CoRR, 2024

A Novel Channel Coding Scheme for Digital Multiple Access Computing.
Proceedings of the IEEE International Conference on Communications, 2024

2023
Blind Federated Learning via Over-the-Air q-QAM.
CoRR, 2023

SumComp: Coding for Digital Over-the-Air Computation via the Ring of Integers.
CoRR, 2023

Blind Asynchronous Goal-Oriented Detection for Massive Connectivity.
Proceedings of the 21st International Symposium on Modeling and Optimization in Mobile, 2023

Computing Functions Over-the-Air Using Digital Modulations.
Proceedings of the IEEE International Conference on Communications, 2023

Off-the-grid Blind Deconvolution and Demixing.
Proceedings of the IEEE Global Communications Conference, 2023

Optimal Receive Filter Design for Misaligned Over-the-Air Computation.
Proceedings of the IEEE Globecom Workshops 2023, 2023

2022
A Novel Demixing Algorithm for Joint Target Detection and Impulsive Noise Suppression.
IEEE Commun. Lett., 2022

Two-Snapshot DOA Estimation Via Hankel-Structured Matrix Completion.
Proceedings of the IEEE International Conference on Acoustics, 2022

Blind Asynchronous Over-the-Air Federated Edge Learning.
Proceedings of the IEEE Globecom 2022 Workshops, 2022

Single-Snapshot DOA Estimation via Weighted Hankel-Structured Matrix Completion.
Proceedings of the 30th European Signal Processing Conference, 2022

2020
Reconstruction of Binary Shapes From Blurred Images via Hankel-Structured Low-Rank Matrix Recovery.
IEEE Trans. Image Process., 2020

Separation of Nonlinearly Mixed Sources Using End-to-End Deep Neural Networks.
IEEE Signal Process. Lett., 2020


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