Roula Nassif

Submitted for publication (1):

  1. R. Nassif, S. Vlaski, M. Carpentiero, V. Matta, and A. H. Sayed, "Differential error feedback for communication-efficient decentralized learning," Submitted for publication, June 2024. [arXiv]

Journal publications (12):

  1. R. Nassif, S. Vlaski, M. Carpentiero, V. Matta, M. Antonini, and A. H. Sayed, "Quantization for decentralized learning under subspace constraints," IEEE Transactions on Signal Processing, vol. 71, pp. 2320-2335, Jun. 2023. [arXiv]

  2. F. Hua, R. Nassif, C. Richard, H. Wang, and A. H. Sayed, "Diffusion LMS with Communication Delays: Stability and Performance Analysis," IEEE Signal Processing Letters, vol. 27, pp. 730-734, Apr. 2020. [arXiv]

  3. R. Nassif, S. Vlaski, C. Richard, and A. H. Sayed, "Learning over Multitask Graphs-Part I: Stability Analysis," IEEE Open Journal of Signal Processing, vol. 1, pp. 28-45, Apr. 2020.[arXiv]

  4. R. Nassif, S. Vlaski, C. Richard, and A. H. Sayed, "Learning over Multitask Graphs-Part II: Performance Analysis," IEEE Open Journal of Signal Processing, vol. 1, pp. 46-63, Apr. 2020.[arXiv]

  5. R. Nassif, S. Vlaski, and A. H. Sayed, "Adaptation and learning over networks under subspace constraints--Part II: Performance Analysis," IEEE Transactions on Signal Processing, vol. 68, pp. 2948-2962, Apr. 2020.[arXiv]

  6. R. Nassif, S. Vlaski, and A. H. Sayed, "Adaptation and learning over networks under subspace constraints--Part I: Stability Analysis," IEEE Transactions on Signal Processing, vol. 68, pp. 1346-1360, Jan. 2020.[arXiv]

  7. R. Nassif, S. Vlaski, C. Richard, J. Chen, and A. H. Sayed, "Multitask Learning over Graphs: An Approach for Distributed, Streaming Machine Learning," IEEE Signal Processing Magazine, vol. 37, no. 3, pp. 14-25, May 2020.[arXiv]

  8. Hua, R. Nassif, C. Richard, H. Wang, and A. H. Sayed, "Online distributed learning over graphs with multitask graph-filter models," IEEE Transactions on Signal and Information Processing over Networks, vol. 6, pp. 63-77, Jan. 2020.[arXiv]

  9. R. Nassif, S. Vlaski, C. Richard, and A. H. Sayed, "A Regularization Framework for Learning over Multitask Graphs," IEEE Signal Processing Letters, vol. 26, no. 2, pp. 297-301, Feb. 2019.[pdf]

  10. R. Nassif, C. Richard, A. Ferrari, and A. H. Sayed, "Diffusion LMS for multitask problems with local linear equality constraints," IEEE Transactions on Signal Processing, vol. 65, no. 19, pp. 4979-4993, Oct. 2017.[arXiv]

  11. R. Nassif, C. Richard, A. Ferrari, and A. H. Sayed, "Proximal multitask learning over networks with sparsity-inducing coregularization," IEEE Transactions on Signal Processing, vol. 64, no. 23, pp. 6329-6344, Dec. 2016.[arXiv]

  12. R. Nassif, C. Richard, A. Ferrari, and A. H. Sayed, "Multitask diffusion adaptation over asynchronous networks," IEEE Transactions on Signal Processing, vol. 64, no. 11, pp. 2835-2850, Jun. 2016.[arXiv]

Inproceedings (29):

  1. R. Nassif, M. Carpentiero, S. Vlaski, V. Matta, and A. H. Sayed, "Matching centralized learning performance via compressed decentralized learning with error feedback," Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Lucca, Italy, Sep. 2024.

  2. S. Vlaski and R. Nassif, "Nonconvex Multitask Learning over Networks," Proc. European Signal Processing Conference (EUSIPCO), Lyon, France, Aug. 2024.

  3. R. Nassif, S. Vlaski, M. Carpentiero, V. Matta, and A. H. Sayed, "Differential error feedback for communication-efficient decentralized optimization," Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Corvallis, OR, USA, Jul. 2024.[pdf]

  4. R. Nassif, S. Kar, and S. Vlaski, "Learning dynamics of low-precision clipped SGD with momentum," Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr. 2024.[pdf]

  5. S Wadehra, R. Nassif, S Vlaski, "Exact Subspace Diffusion for Decentralized Multitask Learning," IEEE Conference on Decision and Control (CDC), Singapore, Dec. 2023. [pdf]

  6. X. Sun, R. Nassif, C. Richard, and H. Wang, "Anomaly Detection in Graph Signals with Canonical Correlation Analysis," Proc. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Herradura, Costa Rica, Dec. 2023. [pdf]

  7. M. Issa, R. Nassif, E. Rizk, and A. H. Sayed, "Decentralized semi-supervised learning over multitask graphs," Proc. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Oct. 2022. [pdf]

  8. R. Nassif, S. Vlaski, M. Antonini, M. Carpentiero, V. Matta, and A. H. Sayed, "Finite bit quantization for decentralized learning under subspace constraints," Proc. European Signal Processing Conference (EUSIPCO), Belgrade, Sep. 2022.[pdf]

  9. R. Nassif, V. Bordignon, S. Vlaski, and A. H.  Sayed, "Decentralized learning in the presence of low-rank noise," Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, May 2022. [arXiv]

  10. R. Nassif, S. Vlaski, C. Richard, and A. H. Sayed, "A Regularization Framework for Learning over Multitask Graphs," Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020. [pdf]

  11. R. Nassif, S. Vlaski, and A. H. Sayed, "Distributed Learning over Networks under Subspace Constraints," Proc. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Nov. 2019. [pdf]

  12. M. Moscu, R. Nassif, F. Hua, and C. Richard, "Apprentissage distribué de la topologie d'un graphe à partir de signaux temporels sur graphe," Actes du 27e Colloque GRETSI sur le Traitement du Signal et des Images, Lille, France, Aug. 2019. [pdf]

  13. M. Moscu, R. Nassif, F. Hua, and C. Richard, "Learning Causal Networks Topology from Streaming Graph Signals," Proc. IEEE 27th European Signal Processing Conference (EUSIPCO), Coruña, Spain, 2019. [pdf]

  14. R. Nassif, S. Vlaski, and A. H. Sayed, "Distributed inference over networks under subspace constraints," Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 2019. [pdf]

  15. F. Hua, R. Nassif, C. Richard, H. Wang, and A. H. Sayed, "Decentralized clustering for node-variant graph filtering with graph diffusion LMS," Proc. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Oct. 2018. [pdf]

  16. F. Hua, R. Nassif, C. Richard, H. Wang, and A. H. Sayed, "A Preconditioned Graph Diffusion LMS for Adaptive Graph Signal Processing," Proc. IEEE 26th European Signal Processing Conference (EUSIPCO), Rome, Italy, Sep. 2018. [pdf]

  17. R. Nassif, S. Vlaski, and A. H. Sayed, "Distributed Inference over Multitask Graphs under Smoothness," Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Kalamata, Greece, Jun. 2018. [pdf]

  18. S. Vlaski, H. Maretic, R. Nassif, P. Frossard, and A. H. Sayed, "Online Graph Learning from Sequential Data," Proc. IEEE Data Science Workshop, Lausanne, Switzerland, Jun. 2018.[pdf]

  19. R. Nassif, C. Richard, J. Chen, and A.H. Sayed, "Distributed diffusion adaptation over graph signals," Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Alberta, Canada, Apr. 2018.[pdf]

  20. F. Hua, R. Nassif, C. Richard, H. Wang, and J. Huang, "Penalty-based multitask estimation with non-local linear equality constraints", Proc. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Dec. 2017.[pdf]

  21. R. Nassif, C. Richard, J. Chen, and A. H. Sayed, "A Graph Diffusion LMS Strategy for Adaptive Graph Signal Processing," Proc. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Oct. 2017.[pdf]

  22. F. Hua, R. Nassif, C. Richard, H. Wang, and J. Huang, "Penalty-based multitask distributed adaptation over networks with constraints", Proc. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Oct. 2017.[pdf]

  23. R. Nassif, C. Richard, J. Chen, R. Couillet, and P. Borgnat, "Filtrage LMS sur graphe. Algorithme et analyse", Actes du 26e Colloque GRETSI sur le Traitement du Signal et des Images, Nice, France, 2017.[pdf]

  24. R. Nassif, C. Richard, A. Ferrari, and A. H. Sayed, "Distributed learning over multitask networks with linearly related tasks," Proc. Asilomar Conference on Signals, Systems, and Computers, pp. 1390-1394, Pacific Grove, CA, Nov. 2016.[pdf]

  25. R. Nassif, C. Richard, J. Chen, A. Ferrari, and A. H. Sayed, "Diffusion LMS over multitask networks with noisy links," Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4583-4587, Shanghai, China, Mar. 2016.[pdf]

  26. R. Nassif, C. Richard, A. Ferrari, and A. H. Sayed, "Multitask diffuion LMS with sparsity-based regularization," Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3516-3520, Brisbane, Australia, Apr. 2015.[pdf]

  27. R. Nassif, C. Richard, and A. Ferrari, "Estimation distribuée sur les réseaux multitâches en présence d’échanges d’informations bruitées," Actes du 25e Colloque GRETSI sur le Traitement du Signal et des Images, Lyon, France, Sep. 2015.[pdf]

  28. R. Nassif, C. Richard, A. Ferrari, and A. H. Sayed, "Performance analysis of multitask diffusion adaptation over asynchronous networks," Proc. Asilomar Conference on Signals, Systems, and Computers, pp. 788-792, Pacific Grove, CA, Nov. 2014.[pdf]

  29. R. Nassif, S. Destercke, and M. H. Masson, "Classification multi-label par fonctions de croyance," 22èmes Rencontres Francophones sur la Logique Floue et ses Applications (LFA), pp. 119-126, Reims, France, Oct. 2013.