Samaneh Mohammadi
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Västerås
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Samaneh Mohammad joined RISE SICS Västerås as a researcher Ph.D. candidate in Distributed Artificial Intelligence of 2021. Her research interests include Edge Computing, Edge Artificial intelligence, Federated Learning, and Deep Learning.
Samaneh received her Master's degree in Information Technology Engineering from the University of Tehran in Iran in 2020. Her Master's thesis focused on the "Anomaly detection in Dynamic Networks," which use deep learning and inductive learning.
Feel free to visit her LinkedIn https://www.linkedin.com/in/samaneh-mohammadi-22879b159/
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Publikationer
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Publikationer
- Balancing privacy and performance in federated learning : A systematic literatu…
- Balancing Privacy and Accuracy in Federated Learning for Speech Emotion Recogni…
- Optimized Paillier Homomorphic Encryption in Federated Learning for Speech Emot…
- Secure and Efficient Federated Learning by Combining Homomorphic Encryption and…
- Hyperparameters Optimization for Federated Learning System : Speech Emotion Rec…