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Inference over networks

Magazine Papers

  • S. Barbarossa and G. Scutari, “Bio-Inspired Sensor Network Design,” IEEE Signal Processing Magazine, vol. 24, no. 3, pp. 26–35, May 2007 [DOI].

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.
  • M. Maros and G. Scutari, “Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence,” Proc. Conference on Neural Information Processing Systems (NeurIPS), 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.
  • A. Daneshmand, G. Scutari, P. Dvurechensky, A. Gasnikov, “Newton Method over Networks is Fast up to the Statistical Precision,” Proc. International Conference on Machine Learning (ICML 2021), PMLR vol. 139, pp. 2398–2409, 2021.
  • G. Scutari and S. Barbarossa, “Distributed Consensus Over Wireless Sensor Networks Affected by Multipath Fading,” IEEE Trans. on Signal Processing, vol. 56, no. 8, pp. 4100–4110, Aug. 2008 [DOI].
  • G. Scutari, S. Barbarossa, and L. Pescosolido, “Distributed Decision Through Self-Synchronizing Sensor Networks in the Presence of Propagation Delays and Asymmetric Channels,” IEEE Trans. on Signal Processing, vol. 56, no. 4, pp. 1667–1684, April 2008 [DOI].
  • S. Barbarossa and G. Scutari, “Decentralized Maximum-Likelihood Estimation for Sensor Networks Composed of Nonlinearly Coupled Dynamical Systems,” IEEE Trans. on Signal Processing, vol. 55, no. 7, pp. 3456–3470, July 2007 [DOI].

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.
  • S. Barbarossa, G. Scutari, and T. Battisti, “Cooperative Sensing for Cognitive Radio Using Decentralized Projection Algorithms,” Proc. of the 10th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC09), pp. 116–120, June 21–24, 2009, Perugia, Italy.
  • S. Barbarossa, G. Scutari, and T. Battisti, “Distributed Signal Subspace Projection Algorithms with Maximum Convergence Rate for Sensor Networks with Topological Constraints,” Proc. of the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP09), pp. 2893–2896, April 19–24, 2009, Taipei, Taiwan.
  • S. Barbarossa, T. Battisti, L. Pescosolido, S. Sardellitti, and G. Scutari, “Distributed Spatial Smoothing Algorithms for Wireless Sensor Networks Having Fast Convergence and Robustness Against Coupling Noise,” Proc. of the 10th IEEE International Symposium on Spread Spectrum Techniques and Applications (ISSSTA08), pp. 7–11, Aug. 25–28, 2008, Bologna, Italy.
  • L. Pescosolido, S. Barbarossa, and G. Scutari, “Average Consensus Algorithms Robust Against Channel Noise,” Proc. of the 9th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC08), pp. 261–265, July 7–9, 2008, Recife, Brazil.
  • L. Pescosolido, S. Barbarossa, and G. Scutari, “Radar Sensor Networks with Distributed Detection Capabilities,” Proc. of the 2008 IEEE Radar Conference, 5 pages, May 26–30, 2008, Sheraton Golf Parco dei Medici, Rome, Italy.
  • A. Fasano and G. Scutari, “The Effect of Additive Noise on Consensus Achievement in Wireless Sensor Networks,” Proc. of the 2008 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP08), pp. 2277–2280, March 30–April 4, 2008, Las Vegas, NV, USA.
  • G. Scutari and S. Barbarossa, “Optimal Distributed Decision over Wireless Sensor Networks Affected by Multipath Fading,” Proc. of the 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP07), pp. 245–248, Dec. 12–14, 2007, St. Thomas, Virgin Islands, USA.
  • O. Simeone and G. Scutari, “Pulse-coupled distributed PLLs in Heterogeneous Wireless Networks,” Proc. of the 41st Asilomar Conference on Signals, Systems & Computers, pp. 1770–1775, Nov. 4–7, 2007, Pacific Grove, CA, USA.
  • G. Scutari, S. Barbarossa, and L. Pescosolido, “Distributed Decision Through Self-Synchronizing Sensor Networks in the Presence of Propagation Delays and Asymmetric Channels,” Proc. of the 8th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC07), June 17–20, 2007, Helsinki, Finland.
  • S. Barbarossa, G. Scutari, and A. Swami, “Achieving Consensus in Self-Organizing Wireless Sensor Networks: The Impact of Network Topology on Energy Consumption,” Proc. of the 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP07), vol. 2, pp. II-841–II-844, April 15–20, 2007, Honolulu, Hawaii, USA.
  • S. Barbarossa, G. Scutari, and A. Swami, “Distributed Detection and Estimation in Decentralized Sensor Networks: An Overview,” Proc. of the 14th European Signal Processing Conference, Sept. 4–8, 2006, Florence, Italy.
  • G. Scutari, S. Barbarossa, and L. Pescosolido, “Optimal Decentralized Estimation Through Self-Synchronizing Networks in the Presence of Propagation Delays,” Proc. of the 7th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC06), July 2–5, 2006, Cannes, France.
  • S. Barbarossa, G. Scutari, and L. Pescosolido, “Global stability of a Population of Mutually Coupled Oscillators Reaching Global Maximum Likelihood Estimate Through a Decentralized Approach,” Proc. of the 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP06), vol. 4, pp. 385–388, May 14–19, 2006, Toulouse, France.
  • L. Pescosolido, S. Barbarossa, and G. Scutari, “Decentralized Detection and Localization Through Sensor Networks Designed as a Population of Self-Synchronizing Oscillators,” Proc. of the 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP06), vol. 4, pp. 981–984, May 14–19, 2006, Toulouse, France.