6 papers
Cluster-Aware Over-the-Air Federated Learning with Energy-Harvesting Devices: From Global Training to Model Personalization
Furkan Bagci, Busra Tegin, Mohammad Kazemi +1
Federated learning (FL) enables distributed optimization and learning across decentralized edge devices while preserving data privacy, but its performance is fundamentally constrai…
Robust Composite DNA Storage under Sampling Randomness, Substitution, and Insertion-Deletion Errors
Busra Tegin, Tolga M Duman
DNA data storage offers a high-density, long-term alternative to traditional storage systems, addressing the exponential growth of digital data. Composite DNA extends this paradigm…
Capacity Approximations for Insertion Channels with Small Insertion Probabilities
Busra Tegin, Tolga M Duman
Channels with synchronization errors, exhibiting deletion and insertion errors, find practical applications in DNA storage, data reconstruction, and various other domains. Presence…
On the Capacity of Insertion Channels for Small Insertion Probabilities
Busra Tegin, Tolga M Duman
Channels with synchronization errors, such as deletion and insertion errors, are crucial in DNA storage, data reconstruction, and other applications. These errors introduce memory…
Update Estimation and Scheduling for Over-the-Air Federated Learning with Energy Harvesting Devices
Furkan Bagci, Busra Tegin, Mohammad Kazemi +1
We study over-the-air (OTA) federated learning (FL) for energy harvesting devices with heterogeneous data distribution over wireless fading multiple access channel (MAC). To addres…
Over-the-Air Multi-Sensor Inference with Neural Networks Using Memristor-Based Analog Computing
Busra Tegin, Muhammad Atif Ali, Tolga M Duman
Deep neural networks provide reliable solutions for many classification and regression tasks; however, their application in real-time wireless systems with simple sensor networks i…