PUBLICATION LIST (last update: December 2024)

PRE-PRINTS

1. E. Lari, R. Arablouei, V. C. Gogineni, and S. Werner, “Noise-Robust and Resource-Efficient ADMM-based Federated Learning", arXiv:2409.13451
2. E. Lari, R. Arablouei, V. C. Gogineni, and S. Werner, “Resilience in Online Federated Learning: Mitigating Model-Poisoning Attacks via Partial Sharing”, arXiv:2403.13108

CONFERENCE

1. E. Lari, R. Arablouei, N. K. D. Venkategowda, and S. Werner, “Distributed Maximum Consensus over Noisy Links,” in Proc. Eur. Signal Process. Conf., 2024, pp. 2247–2251. [IEEE]
2. E. Lari, R. Arablouei, and S. Werner, “Privacy-Preserving Distributed Nonnegative Matrix Factorization,” in Proc. Eur. Signal Process. Conf., 2024, pp. 1022–1026. [IEEE]
3. E. Lari, V. C. Gogineni, R. Arablouei, and S. Werner, “On the resilience of online federated learning to model poisoning attacks through partial sharing,” in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., 2024, pp. 9201–9205. [IEEE]
4. E. Lari, V. C. Gogineni, R. Arablouei, and S. Werner, “Continual local updates for federated learning with enhanced robustness to link noise,” in Proc. Asia-Pacific Signal Inf. Process. Assoc., 2023, pp. 1199–1203. [IEEE]
5. E. Lari, V. C. Gogineni, R. Arablouei, and S.Werner, “Resource-efficient federated learning robust to communication errors,” in Proc. IEEE Stat. Signal Process. Workshop, 2023, pp. 265–269. [IEEE]