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Sparsity

Journal Papers

  • M. Maros, G. Scutari, Y. Sun, G. Cheng, “Decentralized Sparse Linear Regression via Gradient-Tracking,” J. of Machine Learning Research, vol. 26, no. 197, pp. 1–56, 2025. The order of the first three authors is alphabetical.
  • Y. Ji, G. Scutari, Y. Sun, and H. Honnappa, “Distributed Sparse Regression via Penalization,” J. of Machine Learning Research, vol. 24, no. 272, pp. 1–62, 2023.
  • Y. Ji, G. Scutari, Y. Sun, and H. Honnappa, “Distributed (ATC) Gradient Descent for High-Dimension Sparse Regression,” IEEE Trans. on Information Theory, vol. 69, no. 8, pp. 5253–5276, 2023 [DOI].
  • M. Maros and G. Scutari, “Acceleration in Distributed Sparse Regression,” Proc. Conference on Neural Information Processing Systems (NeurIPS 2022), 2022.
  • M. Maros and G. Scutari, “DGD2: A Linearly Convergent Distributed Algorithm for High-dimensional Statistical Recovery,” Proc. Conference on Neural Information Processing Systems (NeurIPS 2022), 2022.
  • G. Shetty, K. Slavakis, A. Bose, L. Ying, U. Nakarmi, and G. Scutari, “Bi-Linear Modeling of Data Manifolds for Dynamic-MRI recovery,” IEEE Trans. on Medical Imaging, vol. 39, no. 3, pp. 688–702, March 2020 [DOI].
  • P. Di Lorenzo and G. Scutari, “NEXT: In-Network Nonconvex Optimization,” IEEE Trans. on Signal and Information Processing over Networks, vol. 2, no. 2, pp. 120–136, June 2016 [DOI].
    Top 50 downloaded articles in IEEE TSIPN (Dec. 2016 – May 2018).
    Highly cited paper (ISI Web of Knowledge, 2017, 2018, 2019).
  • A. Daneshmand, F. Facchinei, V. Kungurtsev, and G. Scutari, “Hybrid Random/Deterministic Parallel Algorithms for Convex and Nonconvex Big Data Optimization,” IEEE Trans. on Signal Processing, vol. 63, no. 15, pp. 3914–3929, August 2015 [DOI].
    Top 50 downloaded articles in IEEE TSP (July 2015).
  • F. Facchinei, G. Scutari, and S. Sagratella, “Parallel Selective Algorithms for Big Data Optimization,” IEEE Trans. on Signal Processing, vol. 63, no. 7, pp. 1874–1889, April 2015 [DOI].
    Top 10 downloaded articles in IEEE TSP (March 2015)
    Top 50 downloaded articles in IEEE TSP (April 2015, May 2015).

Refereed Conference Papers

  • M. Maros and G. Scutari, “A Unified View of Decentralized Algorithms for Sparse Linear Regression,” Proc. of the 2023 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP23), Dec. 10–13, 2023, Los Suenos, Costa Rica.
  • I. Notarnicola, Y. Sun, G. Scutari, and G. Notarstefano, “Distributed Big-Data Optimization via Block Communications,” Proc. of the 2017 IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP17), Dec. 10–13, 2017, Curaçao, Dutch Antilles.
    Best Student Paper Award.
  • Y. Sun and G. Scutari, “Distributed Nonconvex Optimization for Sparse Representation,” Proc. of the 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP17), March 5–9, 2017, New Orleans, USA.
  • Y. Sun, G. Scutari, and D. Palomar, “Distributed Nonconvex Multiagent Optimization Over Time-Varying Networks,” Proc. of the 50th Asilomar Conference on Signals, Systems, and Computers, Nov. 6–9, 2016, Pacific Grove, CA, USA.
  • L. Cannelli, P. Scarponi, G. Scutari, and L. Ying, “A Parallel Algorithm for Compressed Sensing Dynamic MRI Reconstruction,” Proc. of the 23rd Annual Meeting and Exhibition, International Society for Magnetic Resonance in Medicine (ISMRM), May 30–June 5, 2015, Toronto, Ontario, Canada.
  • A. Daneshmand, F. Facchinei, V. Kungurtsev, and G. Scutari, “Flexible Selective Parallel Algorithms for Big Data Optimization,” Proc. of the 48th Asilomar Conference on Signals, Systems, and Computers, pp. 3–7, Nov. 2–5, 2014, Pacific Grove, CA, USA.