Details

Autor(en) / Beteiligte

• Zeulin, Nikita
• Galinina, Olga
• Himayat, Nageen
• Andreev, Sergey

Titel

Coded Distributed Gaussian Process Regression

Ist Teil von

• IEEE communications letters, 2023-01, Vol.27 (1), p.372-376

Ort / Verlag

New York: IEEE

Erscheinungsjahr

2023

Quelle

IEEE Xplore

Beschreibungen/Notizen

• In this letter, we propose a coded load balancing method for distributed Gaussian process regression over heterogeneous wireless networks, where users with diverse computational and communications capabilities may offload excessive training data onto a computationally stronger central server to reduce collaborative processing times. The offloaded data are transformed using random Fourier feature mapping and encoded with a random orthogonal matrix to prevent transmission of raw data. The proposed method is particularly applicable to compute-intensive applications, where users operate with large datasets.