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Nonconvex

Preprints

  • K. Ding, M. Maros, and G. Scutari, “A New Decomposition Paradigm for Graph-structured Nonlinear Programs via Message Passing,” preprint, arXiv:2512.24676, 2025.

Monograph (Lecture Notes)

  • A. Nedić, J.-S. Pang, G. Scutari, and Y. Sun, Multi-agent Optimization. Lecture Notes in Mathematics, Springer Verlag, CIME Subseries, 2018. [link]

Refereed Book Chapters

  • F. Facchinei, V. Kungurtsev, L. Lampariello, and G. Scutari, “Iteration Complexity of a Fixed-Stepsize SQP Method for Nonconvex Optimization with Convex Constraints,” Numerical Analysis and Optimization, Springer Proceedings in Mathematics & Statistics, pp. 109–120, 2021.
  • G. Scutari and Y. Sun, “Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization,” in Multi-agent Optimization, Lecture Notes in Mathematics, Springer Verlag, CIME Subseries, pp. 141–308, 2018 [DOI].

Journal Papers

  • X. Chen, T. Cao, and G. Scutari, “Enhancing Convergence of Decentralized Gradient Tracking under the KL Property,” IEEE Trans. on Automatic Control, early access, 2026 [DOI].
  • M. Maros and G. Scutari, “Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence,” Proc. Conference on Neural Information Processing Systems (NeurIPS), 2023.
  • V. Kungurtsev, M. Morafah, T. Javidi, and G. Scutari, “Decentralized Asynchronous Non-convex Stochastic Optimization on Directed Graphs,” IEEE Trans. on Control of Network Systems, vol. 10, no. 4, pp. 1796–1804, 2023 [DOI].
  • K. Slavakis, G. Shetty, L. Cannelli, G. Scutari, U. Nakarmi, and L. Ying, “Kernel Regression Imputation in Manifolds via Bi-linear Modeling: The Dynamic MRI case,” IEEE Trans. on Computational Imaging, vol. 8, pp. 133–147, 2022 [DOI].
  • F. Facchinei, V. Kungurtsev, L. Lampariello, and G. Scutari, “Diminishing Stepsize Methods for Nonconvex Composite Problems via Ghost Penalties: from the General to the Convex Regular Constrained Case,” Optimization Methods and Software, vol. 37, no. 4, pp. 1242–1268, 2022 [DOI].
  • F. Facchinei, V. Kungurtsev, L. Lampariello, and G. Scutari, “Ghost Penalties in Nonconvex Constrained Optimization: Diminishing Stepsizes and Iteration Complexity,” Mathematics of Operations Research, vol. 46, no. 2, pp. 595–627, 2021 [DOI].
  • L. Cannelli, F. Facchinei, G. Scutari, and V. Kungurtsev, “Asynchronous Optimization over Graphs: Linear Convergence under Error Bound Conditions,” IEEE Trans. on Automatic Control, vol. 66, no. 10, pp. 4604–4619, Oct. 2021 [DOI].
  • I. Notarnicola, Y. Sun, G. Scutari, and G. Notarstefano, “Distributed Big-Data Optimization via Block-wise Gradient Tracking,” IEEE Trans. on Automatic Control, vol. 66, no. 5, pp. 2045–2060, May 2021 [DOI].
  • A. Daneshmand, G. Scutari, and V. Kungurtsev, “Second-order Guarantees of Distributed Gradient Algorithms,” SIAM J. on Optimization, vol. 30, no. 4, pp. 3029–3068, 2020 [DOI].
  • Y. Tian, Y. Sun, and G. Scutari, “Achieving Linear Convergence in Distributed Asynchronous Multiagent Optimization,” IEEE Trans. on Automatic Control, vol. 65, no. 12, pp. 5264–5279, 2020 [DOI].
  • L. Cannelli, F. Facchinei, V. Kungurtsev, G. Scutari, “Asynchronous Parallel Algorithms for Nonconvex Optimization,” Mathematical Programming, vol. 184, pp. 121–154, 2020 [DOI].
  • 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].
  • G. Scutari and Y. Sun, “Distributed Nonconvex Constrained Optimization over Time-varying Digraphs,” Mathematical Programming, vol. 176, pp. 497–544, 2019 [DOI].
    Highly cited paper (ISI Web of Knowledge, 2019, 2020).
  • A. Daneshmand, Y. Sun, G. Scutari, F. Facchinei, and B. Sadler, “Decentralized Dictionary Learning over Time-Varying Digraphs,” J. of Machine Learning Research, vol. 20, no. 139, pp. 1–62, 2019.
  • A. Al-Shuwaili, O. Simeone, A. Bagheri, and G. Scutari, “Joint Uplink/Downlink Optimization for Backhaul-Limited Mobile Cloud Computing with User Scheduling,” IEEE Trans. on Signal and Information Processing over Networks, vol. 3, no. 4, pp. 787–802, Dec. 2017 [DOI].
    Top 50 downloaded articles in IEEE TSP (Feb. 2017–June 2017).
  • G. Scutari, F. Facchinei, and L. Lampariello, “Parallel and Distributed Methods for Constrained Nonconvex Optimization – Part I: Theory,” IEEE Trans. on Signal Processing, vol. 65, no. 8, pp. 1929–1944, April 2017 [DOI].
    Top 50 downloaded articles in IEEE TSP (Feb. 2017 – June 2018).
    Highly cited paper (ISI Web of Knowledge, 2018, 2019).
  • F. Facchinei, L. Lampariello, and G. Scutari, “Feasible Methods for Nonconvex Nonsmooth Problems with Applications in Green Communications,” Mathematical Programming, vol. 164, pp. 55–90, 2017 [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).
  • Y. Yang, G. Scutari, D. Palomar, and M. Pesavento, “A Parallel Stochastic Approximation Method for Nonconvex Multi-Agent Optimization Problems,” IEEE Trans. on Signal Processing, vol. 64, no. 11, pp. 2949–2964, June 2016 [DOI].
  • 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).
  • S. Sardellitti, G. Scutari, and S. Barbarossa, “Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing,” IEEE Trans. on Signal and Information Processing over Networks, vol. 1, no. 2, pp. 89–103, June 2015 [DOI].
    Top 50 downloaded articles in IEEE TSIPN (Dec. 2016–June 2017).
    Highly cited paper (ISI Web of Knowledge, 2016–2019).
    2020 IEEE Signal Processing Society Best Paper Award.
  • 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).
  • G. Scutari, F. Facchinei, P. Song, D. P. Palomar, and J.-S. Pang, “Decomposition by Partial Linearization: Parallel Optimization of Multi-agent Systems,” IEEE Trans. on Signal Processing, vol. 62, no. 3, pp. 641–656, Feb. 2014 [DOI].
    2015 IEEE Signal Processing Society Young Author Best Paper Award.
    Highly cited paper (ISI Web of Knowledge, 2016, 2017, 2018, 2019, 2020).
  • Y. Yang, G. Scutari, P. Song, and D. P. Palomar, “Robust MIMO Cognitive Radio under Interference Temperature Constraints,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 11, pp. 2465–2482, Nov. 2013 [DOI].
  • G. Scutari and J.-S. Pang, “Joint Sensing and Power Allocation in Nonconvex Cognitive Radio Games: Nash Equilibria and Distributed Algorithms,” IEEE Trans. on Information Theory, vol. 59, no. 7, pp. 4626–4661, July 2013 [DOI].
  • J.-S. Pang and G. Scutari, “Nonconvex Games with Side Constraints,” SIAM J. on Optimization, vol. 21, no. 4, pp. 1491–1522, Dec. 2011 [DOI].

Refereed Conference Papers

  • J.-S. Pang and G. Scutari, “Joint Sensing and Power Allocation in Nonconvex Cognitive Radio Games: Quasi Nash Equilibria,” IEEE Trans. on Signal Processing, vol. 61, no. 9, pp. 2366–2382, May 2013 [DOI].
  • Y. Tian, Y. Sun, G. Scutari, and B. Du, “ASY-SONATA: Achieving Linear Convergence in Distributed Asynchronous Multiagent Optimization,” Proc. of the 56th Allerton Conference on Communication, Control, and Computing (Allerton 2018), Oct. 2–5, 2018, Monticello, IL, USA.
  • A. Daneshmand, G. Scutari, and V. Kungurtsev, “Second Order Guarantees of Gradient Algorithms over Networks,” Proc. of the 56th Annual Allerton Conference on Communication, Control, and Computing, Oct. 3–5, 2018, Monticello, IL, USA.
  • I. Notarnicola, Y. Sun, G. Scutari, and G. Notarstefano, “Distributed Big-Data Optimization via Block-Iterative Convexification and Averaging,” Proc. of the 56th IEEE Conference on Decision and Control, Dec. 12–15, 2017, Melbourne, Australia.
  • 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.
  • L. Cannelli, F. Facchinei, V. Kungurtsev, and G. Scutari, “Essentially Cyclic Asynchronous Nonconvex Large-Scale Optimization,” Proc. of the 2017 IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2017), July 3–6, 2017, Sapporo, Japan.
    Best Paper Award runner-up.
  • 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.
  • A. Mokhtari, A. Koppel, G. Scutari, and A. Ribeiro, “Large-scale Nonconvex Stochastic Optimization by Doubly Stochastic Successive Convex Approximation,” Proc. of the 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP17), March 5–9, 2017, New Orleans, USA.
  • A. Daneshmand, Y. Sun, G. Scutari, and F. Facchinei, “D2L: Decentralized Dictionary Learning over Dynamic Networks,” Proc. of the 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP17), March 5–9, 2017, New Orleans, USA.
  • L. Cannelli, F. Facchinei, V. Kungurtsev, and G. Scutari, “Asynchronous Parallel Nonconvex Large-scale Optimization,” Proc. of the 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP17), March 5–9, 2017, New Orleans, USA.
  • A. Daneshmand, G. Scutari, and F. Facchinei, “Distributed Dictionary Learning,” Proc. of the 50th Asilomar Conference on Signals, Systems, and Computers, Nov. 6–9, 2016, Pacific Grove, CA, USA.
  • L. Cannelli, G. Scutari, F. Facchinei, and V. Kungurtsev, “Parallel Asynchronous Lock-Free Algorithms for Nonconvex Big-Data Optimization,” Proc. of the 50th Asilomar Conference on Signals, Systems, and Computers, Nov. 6–9, 2016, Pacific Grove, CA, USA.
    Best Paper Award runner-up (track D). [here]
  • 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.
  • P. Di Lorenzo and G. Scutari, “Distributed Nonconvex Optimization Over Time-Varying Networks,” Proc. of the 2016 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP16), March 20–25, 2016, Shanghai, China.
  • P. Di Lorenzo and G. Scutari, “Distributed Nonconvex Optimization Over Networks,” Proc. of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, pp. 229–232, Dec. 13–16, 2015, Cancun, Mexico.
  • S. Sardellitti, S. Barbarossa, and G. Scutari, “Distributed Mobile Cloud Computing: Joint Optimization of Radio and Computational Resources,” Proc. of the 2014 IEEE Global Communications Conference, pp. 1505–1510, Dec. 8–12, 2014, Austin, TX, USA.
  • 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.
  • S. Sardellitti, G. Scutari, and S. Barbarossa, “Distributed Joint Optimization of Radio and Computational Resources for Mobile Cloud Computing,” Proc. of the 3rd IEEE International Conference on Cloud Networking, pp. 211–216, Oct. 8–10, 2014, Luxembourg.
  • G. Scutari, F. Facchinei, L. Lampariello, and P. Song, “Parallel and Distributed Methods for Nonconvex Optimization,” Proc. of the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP14), pp. 840–844, May 4–9, 2014, Florence, Italy.
  • S. Sardellitti, G. Scutari, and S. Barbarossa, “Joint Cell Selection and MIMO Precoding in Heterogeneous Networks via Successive Convex Approximation,” Proc. of the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP14), pp. 850–854, May 4–9, 2014, Florence, Italy.
  • Y. Yang, G. Scutari, and D. Palomar, “Parallel Stochastic Decomposition Algorithms for Multi-Agent Systems,” Proc. of the 14th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC13), pp. 180–184, June 16–19, 2013, Darmstadt, Germany.
  • G. Scutari, F. Facchinei, P. Song, D. Palomar, and J.-S. Pang, “Decomposition by Partial Linearization in Multiuser Systems,” Proc. of the 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP13), pp. 4424–4428, May 26–31, 2013, Vancouver, Canada.
  • I. Atzeni, L. Ordonez, G. Scutari, D. Palomar, and J. Fonollosa, “Cooperative Day-Ahead Bidding Strategies for Demand-side Expected Cost Minimization,” Proc. of the 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP13), pp. 5224–5228, May 26–31, 2013, Vancouver, Canada.
  • G. Scutari, D. Palomar, F. Facchinei, and J.-S. Pang, “Distributed Dynamic Pricing for MIMO Interfering Multiuser Systems: A Unified Approach,” Proc. of the 5th International Conference on Network Games, Control and Optimization, Oct. 12–14, 2011, Paris, France.