Research and Publications
Main interests:
sparse optimization
polynomial and non-convex optimization
machine learning
system identification
distributed systems
CRISP Google Scholar ResearchGate Porto Polito
Journal papers
J20 S. M. Fosson, Centralized and distributed online learning for sparse time-varying optimization, IEEE Trans. Autom. Control, 2021
J19 S. M. Fosson, V. Cerone, D. Regruto, Sparse linear regression from perturbed data, Automatica, 2020
J18 D. Valsesia, S. M. Fosson, C. Ravazzi, T. Bianchi, E. Magli, Analysis of SparseHash: An efficient embedding of set-similarity via sparse projections, Pattern Recognition Lett., 128, pp.93-99, Dec. 2019
J17 S. M. Fosson, M. Abuabiah, Recovery of Binary Sparse Signals from Compressed Linear Measurements via Polynomial Optimization, IEEE Signal Process. Lett., 26(7), pp.1070-1074, Jul. 2019
J16 S. M. Fosson, A biconvex analysis for Lasso ℓ1 reweighting, IEEE Signal Process. Lett., 25(12), pp.1795-1799, Dec. 2018
J15 C. Ravazzi, S. M. Fosson, T. Bianchi and E. Magli, Sparsity estimation from compressive projections via sparse random matrices, EURASIP J. Adv. Signal Process., Dec. 2018
J14 A. Fiandrotti, S. M. Fosson, C. Ravazzi and E. Magli, GPU-Accelerated Algorithms for Compressed Signals Recovery with Application to Astronomical Imagery Deblurring, Int. J. Remote Sens., 39(7), pp. 2043-2065, Jul. 2017
J13 G. Fracastoro, S. M. Fosson and E. Magli, Steerable Discrete Cosine Transform, IEEE Trans. Image Process., 26(1), pp. 303-314, Jan. 2017
J12 S. M. Fosson, J. Matamoros, C. Antón-Haro, and E. Magli, Distributed recovery of jointly sparse signals under communication constraints, IEEE Trans. Signal Process., 64(13), pp. 3470-3482, Jul. 2016
J11 L. Gallana, F. Fraternale, M. Iovieno, S. M. Fosson, E. Magli, M. Opher, J.D. Richardson, D. Tordella, Voyager 2 solar plasma and magnetic field spectral analysis for intermediate data sparsity, JGR - Space Physics, 121(5), pp. 3905-3918-3482, May 2016
J10 C. Ravazzi, S. M. Fosson, E. Magli, Randomized algorithms for distributed nonlinear optimization under sparsity constraints, IEEE Trans. Signal Process., 64(6), pp. 1420-1434, Mar. 2016
J9 J. Matamoros, S.M. Fosson, E. Magli, C. Antón-Haro, Distributed ADMM for in-network reconstruction of sparse signals with innovations, IEEE Trans. Signal Inf. Process. Netw., 1(4), pp. 225-234, Dec. 2015
J8 A. Bay, D. Carrera , S.M. Fosson , P. Fragneto, M. Grella,, C. Ravazzi, E. Magli, Block-sparsity based localization in wireless sensor networks, EURASIP J. Wirel. Commun. Netw., 2015(1), pp. 1-15, Jun. 2015
J7 C. Ravazzi, S. M. Fosson, E. Magli, Distributed iterative thresholding for $l_0/l_1$-regularized linear inverse problems, IEEE Trans. Inf. Theory, 61(4), pp. 2081-2100, Apr. 2015
J6 F. Fagnani, S. M. Fosson, Analysis of reduced-search BCJR algorithms for input estimation in a jump linear system, Signal Process. (Elsevier), 108, pp. 341-350, Mar. 2015
J5 F. Fagnani, S. M. Fosson, C. Ravazzi, Some introductory notes on random graphs, Lecture Notes in Mathematics, 2141, pp. 1-26, 2015
J4 F. Fagnani, S. M. Fosson, C. Ravazzi, Consensus-like algorithms for estimation of Gaussian mixtures over large scale networks, Math. Mod. Meth. Appl. Sci., 24(2), pp. 1-21, Feb. 2014
J3 F. Fagnani, S. M. Fosson, C. Ravazzi, A distributed classification/estimation algorithm for sensor networks, SIAM J. Control Optim., 52(1), pp. 189-218, Jan. 2014
J2 S. M. Fosson, Binary input reconstruction for linear systems: A performance analysis. Fosson, Nonlinear Anal. Hybrid Syst., 7(1), pp. 54-67, Feb 2013
J1 S. M. Fosson, A Decoding Approach to Fault Tolerant Control of Linear Systems with Quantized Disturbance Input, Int. J. Control, 84(11), pp. 1779-1795, 2011
Conference papers
C39 V. Cerone, S. M. Fosson, S. Pirrera, D. Regruto, Alternating direction method of multipliers for polynomial optimization, ECC, 2023
C38 V. Cerone, S. M. Fosson, S. Pirrera, D. Regruto, Set-membership identification of continuous-time systems through model transformation, CDC, 2022
C37 V. Cerone, S. M. Fosson, D. Regruto, A Non-Convex Adaptive Regularization Approach to Binary Optimization, CDC, 2021
C36 S. M. Fosson, V. Cerone , D. Regruto, T. Abdalla, A concave approach to errors-in-variables sparse linear system identification, IFAC SysID, 2021
C35 S. M. Fosson, D. Regruto, T. Abdalla, A. Salam, A convex optimization approach to online set-membership EIV identification of LTV systems, SICE, 2021
C34 V. Cerone, S. M. Fosson, D. Regruto, A. Salam, Sparse learning with concave regularization: relaxation of the irrepresentable condition, CDC, 2020
C33 V. Cerone, S. M. Fosson, D. Regruto, T. Abdalla, A recursive approach for set-membership EIV identification of LTV systems with bounded variation, CDC, 2020
C32 V. Cerone, S. M. Fosson, D. Regruto, A. Salam, Bode envelope bounds computation for linear time-invariant systems affected by semialgebraic parametric uncertainty, IEEE ICCA, 2020
C31 V. Cerone, S. M. Fosson, D. Regruto, Enhancing low-rank solutions in semidefinite relaxations of Boolean quadratic problems, IFAC WC, 2020
C30 V. Cerone, S. M. Fosson, D. Regruto, Sparse linear regression with compressed and low-precision data via concave quadratic programming, CDC, Nice (France), 2019
C29 V. Cerone, S. M. Fosson, D. Regruto, A linear programming approach to sparse linear regression with quantized data, ACC, Philadelphia, PA, 2019
C28 S. M. Fosson, F. Garin, S. Gracy, A. Y. Kibangou, D. Swart, Input and state estimation exploiting input sparsity, ECC, Napoli (Italy), 2019
C27 S. M. Fosson, Online optimization in dynamic environments: a regret analysis for sparse problems, CDC, Miami, FL, 2018
C26 S. M. Fosson, Non-convex approach to binary compressed sensing, Asilomar Conf. Signal Syst. Comput., Pacific Grove, CA, 2018
C25 S. M. Fosson, J. Matamoros, M. Gregori, E. Magli, Online convex optimization meets sparsity, SPARS, Lisbon (Portugal) 2017
C24 R. R. De Lucia, S. M. Fosson and E. Magli, Low-power distributed sparse recovery testbed on wireless sensor networks, MMSP, Montreal, QC, 2016
C23 D. Valsesia, S. M. Fosson, C. Ravazzi, T. Bianchi, E. Magli, SparseHash: Embedding Jaccard Coefficient between Supports of Signals, IEEE Int. Conf. Multimedia and Expo (ICME), Seattle, WA, 2016.
C22 C. Ravazzi, S. M. Fosson, T. Bianchi, E. Magli, Signal sparsity estimation from compressive noisy projections via γ-sparsified random matrices, Shangai (China), 2016
C21 M. Calvo-Fullana, J. Matamoros,C. Antón-Haro, S. M. Fosson, Sparsity - promoting sensor selection with energy harversting constraints, ICASSP, Shangai (China), 2016
C20 A. Bay, D. Carrera, S. M. Fosson, P. Fragneto, M. Grella, C. Ravazzi, E. Magli, Dictionary Design for Sensor Network Localization via Block-Sparsity, MMSP, Xiamen (China), 2015
C19 S.M. Fosson, J. Matamoros, C. Antón-Haro, E. Magli, Distributed algorithms for in-network recovery of jointly sparse signals, SPARS, Cambridge (UK), 2015
C18 J. Matamoros, S. M. Fosson, E. Magli, and C. Antón-Haro, In-network reconstruction of jointly sparse signals with ADMM, EUCNC 2015
C17 S. M. Fosson, E. Magli, Compressed sensing: basics and beyond (tutorial), EUROCAST 2015
C16 F. Fraternale, L. Gallana,S. M. Fosson, E. Magli, M. Opher, J.D. Richardson, M. Iovieno, and D. Tordella, Solar wind spectral analysis in heliosheath fromVoyager data, 15th European Turbulence Conference, 2015
C15 F. Fraternale, L. Gallana, M. Iovieno, S. M. Fosson, E. Magli, D. Tordella, M. Opher, and J.D. Richardson, Spectral Analysis in the Solar Wind andHeliosheath, 14th Annual International Astrophysics Conference, 2015
C14 F. Fraternale, L. Gallana, M. Iovieno, S. M. Fosson, E. Magli, J.D. Richardson, R. Morgan, and D. Tordella, Turbulence in the Heliosheath: spectral analysisfrom Voyager 1 and 2 data, 68th American Physical Society - Division of Fluid Dynamics Annual Meeting, 2015
C13 J. Matamoros, S. Fosson, E. Magli, C. Antón-Haro, Distributed ADMM for in-network reconstruction of sparse signals with innovations , GlobalSIP, Atlanta (USA), 2014
C12 F. Fraternale, L. Gallana,M. Iovieno, S.M. Fosson, E. Magli, M. Opher, J.D. Richardson , D. Tordella, Spectra and correlations in the solar wind from Voyager 2 around 5AU, 67th Annual Meeting of the APS Division of Fluid Dynamics, San Francisco (USA), 2014
C11 S. M. Fosson, J. Matamoros, C. Antón-Haro, E. Magli, Distributed support detection of jointly sparse signals, ICASSP, Florence (Italy), 2014
C10 C. Ravazzi, S. M. Fosson, E. Magli, Energy-saving gossip algorithm for compressed sensing in multi-agent systems, ICASSP, Florence (Italy), 2014
C9 C. Ravazzi, S. M. Fosson, E. Magli, Distributed soft thresholding for sparse signal recovery, IEEE-Globecom, Atlanta, GA, 2013
C8 A. Fiandrotti, S. M. Fosson, C. Ravazzi, E. Magli, PISTA: Parallel Iterative Soft Thresholding Algorithm for Sparse Image Recovery, PCS, San Jose (USA), 2013
C7 A. Bay, P. Fragneto, M. Grella, S. M. Fosson, C. Ravazzi, E. Magli, Sparsity-based Indoor Localization in Wireless Sensor Networks, Demo Session at MMSP, Pula (Italy), 2013
C6 F. Fagnani, S. M. Fosson, C. Ravazzi, A large scale analysis of a classification algorithm over sensor networks, CDC, Maui (Hawaii), 2012
C5 F. Fagnani, S. M. Fosson, and C. Ravazzi, Input driven consensus algorithm for distributed estimation and classification in sensor networks, CDC, pp. 6654-6659, Orlando, FL, 2011
C4 S. M. Fosson, Analysis of a Deconvolution Algorithm for quantized-input linear systems through Iterated Random Functions, IFAC World Congress, pp. 11302-11302, Milan (Italy), 2011
C3 S. M. Fosson, P. Tilli, Deconvolution of quantized-input linear systems: Analysis via Markov Processes of a low-complexity algorithm, MTNS, pp. 59-66, 2010
C2 F. Fagnani, S. M. Fosson, An information theoretic approach to hybrid deconvolution problems, IFAC World Congress, pp. 10112-10117, Seoul (South Korea), 2008
C1 L. Galleani, L. Lo Presti, and S. M. Fosson, The Wigner spectrum and its application to stochastic processes, IEEE-EURASIP NSIP 03, Grado, 2003