Publications

Journal papers

Submitted

• 1. C. Battiloro, L. Testa, L. Giusti, S. Sardellitti, P. Di Lorenzo, and S. Barbarossa, Generalized Simplicial Attention Neural Networks, submitted to IEEE Transactions on Signal and Information Processing over Networks, 2023.

  2. K. Katsanos, P. Di Lorenzo, G. Alexandropoulos, Multi-RIS-Empowered Multiple Access: A Distributed Sum-Rate Maximization Approach, submitted to IEEE Journal of Selected Topics in Signal Processing, 2024.

Published

• 1. G. D'Acunto, P. Di Lorenzo, F. Bonchi, S. Sardellitti, S. Barbarossa, Learning Multi-Frequency Partial Correlation Graphs, to appear in IEEE Transactions on Signal Processing, 2024.

  2. S. Sardellitti, P. Di Lorenzo, S. Barbarossa, RIS-Aided Wireless Fingerprinting Localization Based on Multilayer Graph Representations, to appear in IEEE Communications Letters, 2024.

  3. F. Binucci, P.  Banelli, P. Di Lorenzo, S. Barbarossa, Opportunistic Information-Bottleneck for Goal-oriented Feature Extraction and Communication, IEEE Open Journal of the Communications Society, vol. 5, pp. 2418 - 2432, April  2024. 

  4. C. Battiloro, Z. Wang, H. Riess, P.  Di Lorenzo, A. Ribeiro, Tangent Bundle Convolutional Learning: From Manifolds to Cellular Sheaves and Back, IEEE Transactions on Signal Processing, vol. 72, pp. 1892-1909, March 2024.

  5. M. Polverini, S. Sardellitti, S. Barbarossa, A. Cianfrani, P. Di Lorenzo, M. Listanti, Reducing the In band Network Telemetry overhead through the spatial sampling: Theory and experimental results. Computer Networks, Feb. 2024. 

  6. P. Di Lorenzo, M. Merluzzi, F. Binucci, C. Battiloro, P. Banelli, E. Calvanese Strinati, S. Barbarossa, Goal-oriented Communications for the IoT: System Design and Adaptive Resource Optimization, IEEE Internet of Things Magazine, vol. 6, no. 4, December 2023.

  7. F. Binucci, P. Banelli, P. Di Lorenzo, and S. Barbarossa, Multi-user Goal-oriented Communications with Energy-efficient Edge Resource Management, IEEE Transactions on Green Communications and Networking, vol.7, no.4, pp. 1709-1724, December 2023.

  8. Sergio Barbarossa, Danilo Comminiello, Eleonora Grassucci, Francesco Pezone, Stefania Sardellitti, Paolo Di Lorenzo, Semantic Communications Based on Adaptive Generative Models and Information Bottleneck, IEEE Communications Magazine, vol. 61, no.11, pp. 36-41, November 2023.

  9. G. D'Acunto, P. Di Lorenzo, and S. Barbarossa, Multiscale Causal Structure Learning, Transactions on Machine Learning Research, October 2023.

  10. G. Alexandropoulos; Dinh-Thuy Phan-Huy; K. Katsanos; M. Crozzoli; H. Wymeersch; P. Popovski; P. Ratajczak; Y. Benedic; M. Hamon; S. Herraiz Gonzalez; P. Mursia; M. Rossanese; V. Sciancalepore; J.-B. Gros; S. Terranova; G. Gradoni; P. Di Lorenzo; M. Rahal; B. Denis; R. D’Errico; A. Clemente; E. Calvanese Strinati, RIS-Enabled Smart Wireless Environments: Deployment Scenarios, Network Architecture, Bandwidth and Area of Influence, EURASIP Journal on Wireless Communications and Networking, n. 103, October 2023.

  11. C. Battiloro, P. Di Lorenzo, M. Merluzzi, and S. Barbarossa, Lyapunov-based Optimization of Edge Resources for Energy-Efficient Adaptive Federated Learning, IEEE Transactions on Green Communications and Networking, vol.7, no. 3, pp. 265-280, March 2023.

  12. F. Binucci, P. Banelli, P. Di Lorenzo, and S. Barbarossa, Adaptive Resource Optimization for Edge Inference with Goal-Oriented Communications, EURASIP Journal on Advances in Signal Processing, n.123, December 2022.

  13. P. Di Lorenzo, M. Merluzzi, E. Calvanese Strinati, and S. Barbarossa, Dynamic Edge Computing empowered by Reconfigurable Intelligent Surfaces,  EURASIP Journal on Wireless Communications and Networking, n.122, December 2022.

  14. M. Merluzzi, N. Di Pietro, P. Di Lorenzo, E. Calvanese Strinati, and S. Barbarossa, Discontinuous Computation Offloading for Energy-Efficient Mobile Edge Computing, IEEE Transactions on Green Communications and Networking,  vol. 6, no. 2, June 2022.

  15. C. Battiloro, P. Di Lorenzo, P. Banelli, and S. Barbarossa, Dynamic Resource Allocation for Decentralized Estimation in Energy Harvesting IoT Networks, IEEE Internet of Things Journal, vol. 8, no. 10, pp. 8530-8542  May 2021.

  16. M. Merluzzi, P. Di Lorenzo, and S. Barbarossa, Wireless Edge Machine Learning: Resource Allocation and Trade-offs, IEEE Access, vol. 9, pp. 45377-45398, March 2021.

  17. S. Scardapane, I. Spinelli, and P. Di Lorenzo, Distributed Training of Graph Convolutional Networks, IEEE Transactions on Signal and Information Processing over Networks, vol. 7, pp. 87-100, 2021.

  18. E. Isufi, P. Banelli, P. Di Lorenzo, and G. Leus, Observing and Tracking Bandlimited Graph Processes from Sampled Measurements, Signal Processing, vol. 177, Dec. 2020.

  19. P. Di Lorenzo, S. Barbarossa, and S. Sardellitti, Distributed Signal Processing and Optimization based on In-Network Subspace Projections, IEEE Transactions on Signal Processing, vol. 68, no. 1, pp. 2061-2076, Dec. 2020. 

  20. M. Merluzzi, P. Di Lorenzo, S. Barbarossa, and V. Frascolla, Dynamic Computation Offloading in Multi-Access Edge Computing via Ultra-Reliable and Low-Latency Communication, IEEE Transactions on Signal and Information Processing over Networks, vol. 6, no. 1, pp. 342-356, Dec. 2020.

  21. S. Colonnese, P. Di Lorenzo, T. Cattai, G. Scarano, and F. De Vico Fallani, A Joint Markov Model for Communities, Connectivity and Signals defined over Graphs, IEEE Signal Processing Letters, vol. 27, pp. 1160-1164, June 2020.

  22. R. Altilio, P. Di Lorenzo, and M. Panella, Distributed Data Clustering over Networks, Pattern Recognition, vol. 93, pp. 603-620, Sept. 2019.

  23. S. Sardellitti, S. Barbarossa, and P. Di Lorenzo, Graph Topology Inference based on Sparsifying Transform Learning, IEEE Transactions on Signal Processing, vol. 67, no. 7, pp. 1712-1717, Apr. 2019.

  24. S. Scardapane and P. Di Lorenzo, Stochastic Training of Neural Networks via Successive Convex Approximations, IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 10, pp. 4947-4956,  Oct. 2018.

  25. P. Di Lorenzo, P. Banelli, E. Isufi, S. Barbarossa, and G. Leus, Adaptive Graph Signal Processing: Algorithms and Optimal Sampling Strategies, IEEE Transactions on Signal Processing, vol. 66, no. 13, pp. 3584-3598, July 2018 .

  26. S. Sardellitti, S. Barbarossa, and P. Di Lorenzo, On the Graph Fourier Transform for Directed Graphs, IEEE Journal of Selected Topics in on Signal Processing, vol. 11, no. 6, Sept. 2017.

  27. P. Di Lorenzo, P. Banelli, S. Barbarossa, and S. Sardellitti, Distributed Adaptive Learning of Graph Signals, IEEE Transactions on Signal Processing, vol. 65, no. 16, pp. 4193-4208, Aug. 2017.

  28. S. Scardapane and P. Di Lorenzo, A Framework for Parallel and Distributed Training of Neural Networks, Neural Networks, Vol. 91, pp. 42-54, July 2017.

  29. P. Di Lorenzo, S. Barbarossa, P. Banelli, and S. Sardellitti, Adaptive Least Mean Squares Estimation of Graph Signals, IEEE Transactions on Signal and Information Processing over Networks, vol. 2, no. 4, Dec. 2016.

  30. M. Tsitsvero, S. Barbarossa, and P. Di Lorenzo, Signals on Graphs: Uncertainty Principle and Sampling, IEEE Transactions on Signal Processing, vol. 64, no. 18, pp. 4845-4860, Sept. 2016.

  31. S. Scardapane, R. Fierimonte, P. Di Lorenzo, M. Panella, and A. Uncini, Distributed Semi-supervised Support Vector Machines, Neural Networks, vol. 80, pp. 43-52, Aug. 2016.

  32. P. Di Lorenzo and G. Scutari, NEXT: In-Network Nonconvex Optimization, IEEE Transactions on Signal and Information Processing over Networks, vol. 2, no. 2, pp. 120-136, June 2016.

  33. P. Di Lorenzo, Diffusion Adaptation Strategies for Distributed Estimation over Gaussian Markov Random Fields, IEEE Transactions on Signal Processing, vol. 62, no. 21, pp. 5748-5760, Nov. 2014.

  34. S. Barbarossa, S. Sardellitti, and P. Di Lorenzo, Communicating while Computing: Distributed Mobile Cloud Computing over 5G Heterogeneous Networks, IEEE Signal Processing Magazine, vol. 31, no. 6, pp. 45-55, Nov. 2014.

  35. P. Di Lorenzo and S. Barbarossa, Distributed Estimation and Control of Algebraic Connectivity over Random Graphs, IEEE Transactions on Signal Processing, vol. 62, no. 21, pp. 5615-5628, Nov. 2014.

  36. S. Barbarossa, P. Di Lorenzo, and P. Vecchiarelli, Parameter Estimation of 2D Multi-Component Polynomial Phase Signals: An Application to SAR Imaging of Moving Targets, IEEE Transactions on Signal Processing, vol. 62, no. 17, pp. 4375-4389, Sept. 2014.

  37. P. Di Lorenzo, S. Barbarossa, and Ali H. Sayed, Distributed Spectrum Estimation for Small Cell Networks based on Sparse Diffusion Adaptation, IEEE Signal Processing Letters, vol. 20, no. 12, pp. 1261-1265, December 2013.

  38. P. Di Lorenzo, S. Barbarossa, and Ali H. Sayed, Bio-Inspired Decentralized Radio Access based on Swarming Mechanisms over Adaptive Networks, IEEE Transactions  on Signal Processing, vol. 61, no. 12, pp. 3183-3197, June 2013.

  39. P. Di Lorenzo and S. Barbarossa, Swarming Algorithms for Distributed Radio Resource Allocation, IEEE Signal Processing Magazine, vol. 30, no. 3, pp. 144-154, May 2013.

  40. P. Di Lorenzo and Ali H. Sayed, Sparse Distributed Learning Based on Diffusion Adaptation, IEEE Transactions on Signal Processing, vol. 61, no. 6, pp. 1419-1433, March 2013.

  41. P. Di Lorenzo, S. Barbarossa, and M. Omilipo, Distributed Sum-Rate Maximization over Finite Rate Coordination Links Affected by Random Failures, IEEE Transactions on Signal Processing, vol. 61, no. 3, pp. 648-660, Feb. 2013.

  42. P. Di Lorenzo, S. Barbarossa, and L. Borgarelli, Optimal beamforming for range/Doppler ambiguity minimization in squinted SAR, IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 1, pp. 277-293, Jan. 2013.

  43. P. Di Lorenzo, S. Barbarossa, and Ali H. Sayed, Decentralized resource assignment in cognitive networks based on swarming mechanisms over random graphs, IEEE Transactions on Signal Processing, vol. 60, no.7, pp. 3755-3769, July 2012.

  44. P. Di Lorenzo and S. Barbarossa, A bio-inspired swarming algorithm for decentralized access in cognitive radio, IEEE Transactions on Signal Processing, vol. 59, no.12, pp. 6160-6174, December 2011.

Conference papers

Submitted

1. A. Devoto, S. Petruzzi, J. Pomponi, P. Di Lorenzo, and S. Scardapane, Adaptive Semantic Token Selection for AI-native Goal-oriented Communications, submitted to IEEE SPAWC 2024.

2. K. Katsanos, P. Di Lorenzo, and G. Alexandropoulos, The Interference Broadcast Channel with Reconfigurable Intelligent Surfaces: A Cooperative Sum-Rate Maximization Approach,  submitted to IEEE SPAWC, 2024.

3. N. Hello, P. Di Lorenzo, E. Calvanese Strinati, Semantic Communication Enhanced by Knowledge Graph Representation Learning , submitted to IEEE SPAWC, 2024.

4. L. Di Nino, S. Barbarossa, P. Di Lorenzo, Learning Sheaf Laplacian Optimizing Restriction Maps, submitted to the the Asilomar Conference on Signals, Systems, and Computers, 2024.

5. J. Pomponi, A. Devoto, P. Di Lorenzo, and S. Scardapane, Goal-oriented Communications based on Recursive Early-Exit Neural Networks, submitted to the the Asilomar Conference on Signals, Systems, and Computers, 2024.

Published

• 1. F. Binucci, M. Merluzzi, P. Banelli, E. Calvanese Strinati, P. Di Lorenzo, Enabling Edge Artificial Intelligence via Goal-oriented Deep Neural Network Splitting, Proc. of ISWCS 2024.

  2. L. Marinucci, C. Battiloro, P. Di Lorenzo, Topological Adaptive Learning over Cell Complexes, Proc. of EUSIPCO 2024.

  3. S. Fiorellino, C. Battiloro, E. Calvanese Strinati, P. Di Lorenzo, Dynamic Relative Representations for Goal-Oriented Semantic Communications, Proc. of EUSIPCO 2024.  

  4. T. Papamarkou, T. Birdal, M. Bronstein, G. Carlsson, J. Curry, Y. Gao, M. Hajij, R. Kwitt, P. Liò, P. Di Lorenzo, V. Maroulas, N. Miolane, F. Nasrin, K. Natesan Ramamurthy, B. Rieck, S. Scardapane, M. T Schaub, P. Veličković, B. Wang, Y. Wang, G. Wei, G. Zamzmi, Position Paper: Challenges and Opportunities in Topological Deep Learning, Proc. of ICML, Vienna, Austria, 2024. 

  5. E. Calvanese Strinati, P. Di Lorenzo, V. Sciancalepore, A. Aijaz, M. Kountouris, D. Gunduz, P. Popovski, M. Sana, P. A. Stavrou, B. Soret, N. Cordeschi, S. Scardapane, M. Merluzzi, L. Zanzi, M. Boldi Renato, T. Quek, N. di Pietro, O. Forceville, F. Costanzo, P. Li, Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach, Proc. of EuCNC, Antwerp, Belgium, 2024.

  6. C. Battiloro, I. Spinelli, L. Telyatnikov, M. Bronstein, S. Scardapane, P. Di Lorenzo, From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module, Proc. of ICLR 2024, Vienna, Austria.  

  7. S. Fiorellino, C. Battiloro, P. Di Lorenzo, Topological Neural Networks over the Air, proc. of IEEE ICASSP 2024, Seoul, Korea.

  8. F. Saggese, V. Croisfelt, F. Costanzo, J. Shiraishi, R. Kotaba, P. Di Lorenzo, P. Popovski, Control Aspects for Using RIS in Latency-Constrained Mobile Edge Computing,  proc. of ASILOMAR conference, 2023.

  9. C. Battiloro, P.  Di Lorenzo, A. Ribeiro, Parametric Dictionary Learning for Topological Signal Representation, proc. of EUSIPCO 2023, Helsinki, Finland. 

  10. F. Binucci, P. Banelli, P. Di Lorenzo, S. Barbarossa, Analog versus Digital Pulse Amplitude Modulation for Goal-Oriented Wireless Communications, proc. of EUSIPCO 2023, Helsinki, Finland. 

  11. S. Sardellitti, M. Polverini, S. Barbarossa, A. Cianfrani, P. Di Lorenzo, M. Listanti, In Band Network Telemetry Overhead Reduction Based on Data Flows Sampling and Recovering, Proc. of  ENS 2023, co-hosted at IEEE NetSoft 2023, Madrid, Spain. 

  12. L.Giusti, C. Battiloro, L.Testa, P. Di Lorenzo, S. Sardellitti, S. Barbarossa, Cell Attention Networks, Proc. of IJCNN 2023, preprint arxiv:2209.08179.

  13. D. M. Cinque, C. Battiloro, P. Di Lorenzo, Pooling Strategies for Simplicial Convolutional Networks, Proc. of ICASSP 2023, Rhodes, Greece.

  14. C. Battiloro, P. Di Lorenzo, and S. Barbarossa, Topological Slepians: Maximally Localized Representations of Signals over Simplicial Complexes, Proc. of ICASSP 2023, Rhodes, Greece. 

  15. C. Battiloro, S. Sardellitti, S. Barbarossa, P. Di Lorenzo, Topological Signal Processing over Weighted Simplicial Complexes, Proc. of ICASSP 2023, Rhodes, Greece.

  16. C. Battiloro, Z. Wang, H. Riess, P.  Di Lorenzo, A. Ribeiro, Tangent Bundle Filters and Neural Networks: From Manifolds to Cellular Sheaves and Back, Proc. of ICASSP 2023, Rhodes, Greece.

  17. K. Stylianopoulos, M. Merluzzi, P. Di Lorenzo, and G. C. Alexandropoulos, Lyapunov-Driven Deep Reinforcement Learning For Edge Inference Empowered By Reconfigurable Intelligent Surfaces, Proc. of ICASSP 2023, Rhodes, Greece.

  18. M. Merluzzi, F. Costanzo, K. Katsanos, G. Alexandropoulos, P. Di Lorenzo, Power Minimizing MEC Offloading with QoS Constraints over RIS-Empowered Communications, proc. of IEEE Globecom 2022. 

  19. F. Binucci, P. Banelli, P. Di Lorenzo, S. Barbarossa, Dynamic Resource Allocation for Multi-User Goal-oriented Communications at the Wireless Edge, proc. of Eurasip EUSIPCO, 2022. 

  20. K. Katsanos, P. Di Lorenzo, and G. Alexandropoulos, Distributed Sum-Rate Maximization of Cellular Communications with Multiple Reconfigurable Intelligent Surfaces,  proc. of IEEE SPAWC, 2022.

  21. F. Ezzahra Airod, M. Merluzzi, P. Di Lorenzo, and E. Calvanese Strinati, Reconfigurable Intelligent Surface Aided Mobile Edge Computing over Intermittent mmWave Links, proc. of IEEE SPAWC, 2022.

  22. M. Merluzzi, C. Battiloro, P. Di Lorenzo, E. Calvanese Strinati,  Energy-Efficient Classification at the Wireless Edge with Reliability Guarantees, proc. of IEEE International Conference on Communications (ICC), 2022.

  23. L. Giusti, C. Battiloro, P. Di Lorenzo, and S. Barbarossa, Graph Convolutional Networks with Autoencoder-based Compression and Multi-Layer Graph Learning, proc. of IEEE ICASSP, Singapore, June 2022.

  24. F. Pezone, S. Barbarossa, and P. Di Lorenzo, Goal Oriented Communication for Edge Learning based on the Information Bottleneck,  proc. of IEEE ICASSP, Singapore, June 2022.

  25. C. Battiloro, M. Merluzzi, P. Di Lorenzo, and S. Barbarossa, Dynamic Resource Optimization for Adaptive Federated Learning empowered by Reconfigurable Intelligent Surfaces, proc. of IEEE ICASSP, Singapore, June 2022.

  26. M. Merluzzi, A. Martino, F. Costanzo, P. Di Lorenzo, and S. Barbarossa, Dynamic Ensemble Inference at the Edge, Proc. of IEEE Globecom, Madrid, Spain, Dec. 2021.

  27. P. Di Lorenzo, M. Merluzzi, E. Calvanese Strinati, Dynamic Mobile Edge Computing empowered with Reconfigurable Intelligent Surfaces, Proc. of  IEEE SPAWC, Lucca, Italy, Sept. 2021.

  28. E. Calvanese Strinati, G. C. Alexandropoulos, V. Sciancalepore , M. Di Renzo , H. Wymeersch, D. Phan-huyk, M. Crozzoli, R. D’Errico, E. De Carvalho, P. Popovski, P. Di Lorenzo, L. Bastianelli, M. Belouar, J. E. Mascolo, G. Gradoni, S. Phang , G. Lerosey , Benoıt Denis, Wireless Environment as a Service Enabled by Reconfigurable Intelligent Surfaces: The RISE-6G Perspective,  Proc. of EUCNC 6G Summit, Porto, Portugal, June 2021. 

  29. P. Di Lorenzo, C. Battiloro, M. Merluzzi, S. Barbarossa, Dynamic Resource Optimization for Adaptive Federated Learning at the Wireless Network Edge, Proc. of  IEEE ICASSP, Toronto, Canada, 2021.

  30. S. Sardellitti, S. Barbarossa, P. Di Lorenzo, Online Learning of Time-varying Signals and Graphs,  Proc. of  IEEE ICASSP, Toronto, Canada, 2021.

  31. C. Battiloro and P. Di Lorenzo, Distributed Tensor Completion over Networks, Proc. of ICASSP, Barcelona, May 2020.

  32. M. Merluzzi, P. Di Lorenzo, and S. Barbarossa, Dynamic Resource Allocation for Wireless Edge Machine Learning with Latency and Accuracy Guarantees, Proc. of ICASSP, Barcelona, May 2020.

  33. F. Costanzo, P. Di Lorenzo, and S. Barbarossa, Dynamic Resource Optimization and Altitude Selection in UAV-based Multi-Access Edge Computing, Proc. of ICASSP, Barcelona, May 2020.

  34. M. Merluzzi, N. Di Pietro, P. Di Lorenzo, E. Calvanese Strinati, S. Barbarossa, Network Energy Efficient Mobile Edge Computing with Reliability Guarantees, Proc. of IEEE Globecom, Hawaii, Dec. 2019.

  35. Paolo Di Lorenzo, Sergio Barbarossa, and Stefania Sardellitti, Distributed Adaptive Learning of Graph Processes via In-Network Subspace Projections, Proc. of the Asilomar Conference on Signals, Systems and Computers, Pacific Grove, Nov. 2019.

  36. Paolo Di Lorenzo and Simone Scardapane, Distributed Stochastic Nonconvex Optimization and Learning based on Successive Convex Approximation, Proc. of the Asilomar Conference on Signals, Systems and Computers, Pacific Grove, Nov. 2019.

  37. S. Sardellitti, S. Barbarossa, P. Di Lorenzo, Enabling Prediction via Multi-Layer Graph Inference and Sampling, Proc. of SAMPTA, Bordeaux, July 2019. 

  38. M. Merluzzi, P. Di Lorenzo, S. Barbarossa, and V. Frascolla, Joint Resource Allocation for Latency-Constrained Dynamic Computation Offloading with  MEC, Proc. of IEEE WCNC, Marrakech, 2019.

  39. M. Merluzzi, P. Di Lorenzo, S. Barbarossa, Latency-Constrained Dynamic Computation Offloading with Energy Harvesting IoT Devices, Proc. of IEEE INFOCOM, Paris, 2019.

  40. P. Di Lorenzo, S. Barbarossa, and S. Sardellitti, Distributed Signal Recovery based on In-Network Subspace Projections, Proc. of IEEE ICASSP, Brighton, 2019.

  41. P. Di Lorenzo, C. Battiloro, P. Banelli, and S. Barbarossa, Dynamic Resource Optimization for Decentralized Signal Estimation in Energy Harvesting Wireless Sensor Networks, Proc. of IEEE ICASSP, Brighton, 2019.

  42. M. Merluzzi, P. Di Lorenzo, and S. Barbarossa, Dynamic Joint Resource Allocation and User Assignment in Multi-Access Edge Computing, Proc. of IEEE ICASSP, Brighton, 2019.

  43. E. Isufi, P. Banelli, P. Di Lorenzo, and G. Leus, Observing Bandlimited Graph Processess from Subsampled Measurements, Proc. of Asilomar Conference on Signals, Systems, and Computers, 2018.

  44. P. Di Lorenzo, E. Ceci, Online Recovery of Time-varying Signals Defined over Dynamic Graphs, Proc. of European Signal Processing Conference, Rome, Italy, Sept. 2018.

  45. E. Isufi, P. Di Lorenzo, P. Banelli, and G. Leus, Distributed Wiener-based Reconstruction of Graph Signals, Proc. of IEEE Statistical Signal Processing Workshop, Freiburg, Germany, 2018.

  46. P. Di Lorenzo, S. Barbarossa, and P. Banelli, Optimal Power and Bit Allocation for Graph Signal Interpolation, IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 2018.

  47. P. Di Lorenzo, P. Banelli, S. Barbarossa, Optimal Sampling Strategies for Adaptive Learning of Graph Signals, Proc. of EURASIP Eusipco, Kos, Greece, Aug.-Sept. 2017.

  48. P. Di Lorenzo, E. Isufi, P. Banelli, S. Barbarossa, G. Leus, Distributed Recursive Least Squares Strategies for Adaptive Reconstruction of Graph Signals, Proc. of EURASIP  Eusipco, Kos, Greece, Aug.-Sept. 2017.

  49. S. Sardellitti, S. Barbarossa, P. Di Lorenzo, Graph Fourier Transform for Directed Graphs based on Lovàsz Estension of Min-Cut, Proc. of IEEE ICASSP, New Orleans, USA, 2017.

  50. S. Sardellitti, S. Barbarossa, and P. Di Lorenzo, Graph topology inference based on transform learning, Proc. of IEEE GlobalSIP, Washington, Dec. 2016. (Invited paper)

  51. P. Di Lorenzo, S. Barbarossa, P. Banelli, and S. Sardellitti, Distributed Adaptive Learning of Signals defined over Graphs, Proc. of IEEE Asilomar Conference, Pacific Grove, Nov. 2016. (Invited paper)

  52. P. Di Lorenzo and S. Scardapane, Parallel And Distributed Training Of Neural Networks Via Successive Convex Approximation, Proc. of IEEE Workshop on Machine Learning for Signal Processing, Salerno, Sept. 2016.

  53. P. Di Lorenzo, S. Barbarossa, P. Banelli, and S. Sardellitti, LMS Estimation of Signals defined over Graphs, European Signal Processing Conference, Budapest, Aug. 2016.

  54. P. Di Lorenzo and G. Scutari, Distributed Nonconvex Optimization over Time-Varying Networks, Proc. of IEEE Intern. Conference on Acoustics, Speech and Signal Processing, Shangai, China, March 2016. 

  55. P. Di Lorenzo and G. Scutari, Distributed Nonconvex Optimization Over Networks, IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Dec. 2015.

  56. M. Tsitsvero, S. Barbarossa, and P. Di Lorenzo, Uncertainty Principle and Sampling of Signals Defined on Graphs, Proc. of IEEE Asilomar Conference, Pacific Grove, Nov. 2015. (Invited paper)

  57. S. Barbarossa, P. Di Lorenzo, and M. van der Schaar, Network Formation Games based on Conditional Independence Graphs, Proc. of IEEE Intern. Conference on Acoustics, Speec and Signal Processing, Brisbane, 2015.

  58. S. Barbarossa, P. Di Lorenzo, and S. Sardellitti, Computation Offloading Strategies based on Energy Minimization under Computational Rate Constraints, European Conference on  Networks and Communications, Italy, June 2014. 

  59. P. Di Lorenzo and S. Barbarossa, Distributed Least-Mean Squares Strategies for Sparsity-Aware Estimation over Gaussian Markov Random Fields, Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing, Florence, Italy, May 2014.

  60. Eduardo Makhoul, Yu Zhan, Francisco Ceba, Antoni Broquetas, Alasdhair Beaton, Federico Letterio, Stefania Tonetti, Sergio Barbarossa, Paolo Di Lorenzo, Marco Maffei, Fast  Simulation Performance Evaluation of Spaceborne SAR-GMTI Missions for Maritime  Applications, Proc. European Conference on Synthetic Aperture Radar, Berlin, June 2014.

  61. F. Letterio, S. Tonetti, F. Ceba, Y. Zhan, E. Makhoul, A. Broquetas, M. Maffei, S.Barbarossa, P. Di Lorenzo, A. Beaton, Satellite Convoy Scenario For Spaceborn MTI in Sea Clutter, Proc. 1st International Earth Observation Convoy and Constellation Concepts Workshop, ESA-ESTEC, Noordwijk, The Netherlands, October 2013.

  62. P. Di Lorenzo and S. Barbarossa, Distributed control of wireless ad-hoc networks connectivity incorporating realistic channel models, Proc. European Signal Processing Conference, Marrakech, Sept. 2013. (Invited paper)

  63. S. Barbarossa, S. Sardellitti, and P. Di Lorenzo, Joint allocation of computation and communication resources in multiuser mobile cloud computing, Proc. of IEEE Workshop for Signal Processing Advances in Wireless Communications, Darmstadt, June 2013.

  64. S. Barbarossa, S. Sardellitti, and P. Di Lorenzo, Computation offloading for mobile cloud computing based on wide cross-layer optimization, Proc. of the Future Network and Mobile Summit, Lisbon, July 2013.

  65. P. Di Lorenzo and S. Barbarossa, Decentralized estimation and control of algebraic connectivity of random ad-hoc networks, Proc. IEEE Intern. Conference on Acoustics, Speech and Signal Processing, Vancouver, May 2013.

  66. S. Barbarossa, P. Di Lorenzo, P. Vecchiarelli, A. Silvi, and A. Bruner, Parameter Estimation of 2D Polynomial Phase Signals: An Application to Moving Target Imaging with SAR, Proc. IEEE Intern. Conference on Acoustics, Speech and Signal Processing, Vancouver, May 2013.

  67. P. Di Lorenzo, S. Barbarossa, and Ali H. Sayed, Sparse Diffusion LMS for Distributed Adaptive Estimation, Proc. IEEE Intern. Conference on Acoustics, Speech and Signal Processing, pp. 3281-3284, Kyoto, Japan, March 2012.

  68. P. Di Lorenzo, M. Omilipo, and S. Barbarossa, Distributed stochastic pricing for sum-rate maximization in femtocell networks with random graph and quantized communications, Proc. IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Dec. 2011.

  69. P. Di Lorenzo and S. Barbarossa, Optimal beamforming for range/Doppler ambiguity suppression in squinted SAR systems, Proc. IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing, pp. 169-172, San Juan, Dec. 2011. (IEEE Best Student Paper Award)

  70. P. Di Lorenzo, S. Barbarossa, and Ali H. Sayed, Bio-inspired swarming for dynamic radio access based on diffusion adaptation, Proc. European Signal Processing Conference, pp. 402-407, Barcelona, Sept. 2011. (EURASIP Best Student Paper Award)

  71. P. Di Lorenzo, S. Barbarossa, and Ali H. Sayed, A Bio-inspired fast swarming algorithm for dynamic radio access, Proc. Digital Signal Processing Conference, pp. 1-6, Corfù, July 2011. (Invited paper)

  72. P. Di Lorenzo and S. Barbarossa, Bio-Inspired Swarming Models For Decentralized Radio Access Incorporating Random Links And Quantized Communications, Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 5780-5783, Prague, May 2011. (Invited paper)

  73. P. Di Lorenzo and S. Barbarossa, Distributed Resource Allocation In Cognitive Radio Systems Based On Social Foraging Swarms, Proc. IEEE Workshop for Signal Processing Advances in Wireless Communications, pp. 1-5, Marrakech, June 2010. (IEEE Best Student Paper Award)

  74. P. Di Lorenzo, S. Barbarossa, Wireless sensor networks with distributed decision capabilities based on self-synchronization of relaxation oscillators, Proc. of Int. Conference of Wireless Communications and Mobile Computing, Crete, Greece, 2008. 

Book chapters

• 1. P. Di Lorenzo, M. Merluzzi, and S. Barbarossa, Wireless Edge Machine Learning in Beyond 5G Networks, CNIT Technical Report "Machine Learning and 5G/6G Networks: Interplay and Synergies", 2021.

  2. P. Di Lorenzo, S. Barbarossa, and P. Banelli, Sampling and Recovery of Graph Signals, Cooperative and Graph Signal Processing, P. Djuric and C. Richard Eds., Elsevier, 2018.

  3. S. Barbarossa, S. Sardellitti, and P. Di Lorenzo, Distributed Detection and Estimation in Wireless Sensor Networks, Academic Press Library in Signal Proc., Vol. 2, Commun. and Radar Signal Processing, pp. 329-408, 2014.

Ph.D. Dissertation

P. Di Lorenzo, Bio-Inspired dynamic radio access in cognitive networks based on social foraging swarms, Dept. of Information Eng., Electronics, and Telecommunications, Sapienza University of Rome, April 2012. Best PhD Thesis Award 2012, GTTI