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Successive convex approximation

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

  • 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

  • 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].
  • L. Cannelli, F. Facchinei, V. Kungurtsev, G. Scutari, “Asynchronous Parallel Algorithms for Nonconvex Optimization,” Mathematical Programming, vol. 184, pp. 121–154, 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).
  • 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].
  • 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.
  • A. Alvarado, G. Scutari, and J.-S. Pang, “A New Decomposition Method for Multiuser DC-Programming and Its Applications,” IEEE Trans. on Signal Processing, vol. 62, no. 11, pp. 2984–2998, June 2014 [DOI].
  • 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).

Refereed Conference Papers

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.