Publications

  • Valerio De Caro; Claudio Gallicchio; Davide Bacciu, "Federated Adaptation of Reservoirs via Intrinsic Plasticity", October 2022, ZENODO
     
  • Valerio De Caro; Antonio Di Mauro; Davide Bacciu; Claudio Gallicchio, «Communication-Efficient Ridge Regression in Federated», October 2023, ZENODO
     
  • Jakob Valtl; Javier Mendez; Gianfranco Mauro, «Investigation for the Need of Traditional Data-Preprocessing when Applying Artificial Neural Networks to FMCW-Radar Data», August 2017, ZENODO
     
  • Andrea Ceni; Davide Bacciu; Valerio De Caro; Claudio Gallicchio; Luca Oneto, «Improving Fairness via Intrinsic Plasticity in Echo State Networks», October 2023, ZENODO
     
  • Valerio De Caro; Herbert Danzinger; Claudio Gallicchio; Clemens Könczöl; Vincenzo Lomonaco; Mina Marmpena; Sevasti Politi; Omar Veledar; Davide Bacciu, «Prediction of Driver's Stress Affection in Autonomous Driving Simulations», June 2023, ZENODO
     
  • Georg Macher; Siranush Akarmazyan; Eric Armengaud; Davide Bacciu; Calogero Calandra; Herbert Danzinger; Patrizio Dazzi; Charalampos Davalas; Maria Carmela De Gennaro; Angela Dimitriou; Juergen Dobaj; Maid Dzambic; Lorenzo Giraudi; Sylvain Girbal; Dimitrios Michail; Roberta Peroglio; Rosaria Potenza; Farank Pourdanesh; Matthias Seidl; Christos Sardianos;, «Dependable Integration Concepts for Human-Centric AI-Based Systems», August 2021, Link
     
  • Bacciu, Davide; Carta, Antonio; Gallicchio, Claudio; Schmittner, Christoph, «Safety and Robustness for Deep Neural Networks: An Automotive Use Case», July 2023, ZENODO
     
  • Antonio Carta; Giacomo Carfì; Valerio De Caro; Claudio Gallicchio, «Efficient Anomaly Detection on Temporal Data via Echo State Networks and Dynamic Thresholding», July 2023, ZENODO
     
  • Vincenzo Lomonaco; Valerio De Caro; Claudio Gallicchio; Antonio Carta; Christos Sardianos; Iraklis Varlamis; Konstantinos Tserpes; Massimo Coppola; Mina Marmpena; Sevasti Politi; Erwin Schoitsch; Davide Bacciu, «AI-Toolkit: a Microservices Architecture for Low-Code Decentralized Machine Intelligence», June 2023, ZENODO
     
  • Valerio De Caro; Davide Bacciu; Claudio Gallicchio, «Decentralized Plasticity in Reservoir Dynamical Networks for Pervasive Environments», July 2023, | ZENODO
     
  • Achilles Machumilane; Alberto Gotta; Pietro Cassara; Giuseppe Amato; Claudio Gennaro, «Actor-Critic Scheduling for Path-Aware Air-to-Ground Multipath Multimedia Delivery», August 2022, ZENODO
     
  • Kavalionak H.; Carlini E.; Dazzi P.; Ferrucci L.; Mordacchini M.; Coppola M., «Decentralized federated learning and network topologies: an empirical study on convergence», June 2022, Link
     
  • Argentieri L., Gallicchio C., Micheli A., «Input Routed Echo State Networks», October 2022, ZENODO
     
  • Ceni A., Gallicchio C., «Orthogonality in Additive Reservoir Computing», October 2022, ZENODO
     
  • Gallicchio C., «Minimal Euler state network», July 2022, ZENODO
     
  • Dimitris Palyvos-Giannas; Gabriele Mencagli; Papatriantafilou, Marina; Vincenzo Gulisano, «Lachesis: a middleware for customizing OS», December 2021, ZENODO
     
  • Ceni, Andrea, & Gallicchio, Claudio, «Residual Reservoir Computing Neural Networks for Time-series Classification», August 2023, ZENODO
     
  • Gallicchio C., «Diversifying non-dissipative Reservoir Computing dynamics.», August 2023, ZENODO
     
  • Christoph Schmittner; Sebastian Chlup; Korbinian Christl, «Enabling Model-Based Security Engineering - Automated Attack Tree Generation in ThreatGet», May 2023, ZENODO
     
  • Gabriele Mencagli; Dalvan Griebler; Marco Danelutto, «Towards Parallel Data Stream Processing on System-on-Chip CPU+GPU Devices», April 2022, ZENODO
     
  • Palyvos-Giannas D., Mencagli G., Papatriantafilou M., Gulisano V., “Lachesis: A Middleware for Customizing OS Scheduling ofStream Processing Queries” in Middleware '21: Proceedings of the 22nd International Middleware Conference, December 2021 online,  Link
     
  • Dzambic M., Dobaj J., Seidl M., Macher G., «Architectural Patterns for Integrating AI Technology into Safety-Critical Systems», July 2021, Link
     
  • Schlager C., Macher G., «The Cybersecurity Extension for ASPICE - A View from ASPICE Assessors», August 2021, Link
     
  • H. Kavalionak, E.Carlini, P. Dazzi, L. Ferrucci, M. Mordacchini, M. Coppola, “Impact of Network Topology on the Convergence of Decentralized Federated Learning Systems”, 26th IEEE Symposium on Computers and Communications (ISCC 2021), September 5-8, 2021, Athens, Greece. | ZENODO 
     
  • A. Escobar et al., "Frequency Modulated Continuous Wave Radar-Based Navigation Algorithm using Artificial Neural Network for Autonomous Driving“, 4th IEEE International Conference on Intelligent Transportation Systems (ITSC 2021), September 19-22, 2021, Indianapolis, United States. | ZENODO 
     
  • Christos Chronis, Christos Sardianos, Iraklis Varlamis, Dimitrios Michail and Konstantinos Tserpes, “A driving mode personalization system for autonomous driving using reinforcement learning” 5th Pan-Hellenic Conference on Informatics, 26-28 Nov 2021, Volos, Greece. | ZENODO 
     
  • Charalampos Davalas, Dimitrios Michail, Christos Diou, Iraklis Varlamis and Konstantinos Tserpes. “A Cloud-based Continual Learning System for Road Sign Classification in Autonomous Driving”. 1st International Workshop on Pervasive Artificial Intelligence. Hosted by the 2022 IEEE World Congress on Computational Intelligence. | ZENODO 
     
  • Sylvain Girbal, Jimmy Le Rhun, Daniel Gracia Pérez, David Faura. “Safety and Security monitoring convergence at the dawn of Open Hardware”. In the 11th European Conference on Embedded Real Time Software and Systems (ERTS 2022). Jun 2022. | ZENODO
     
  • S. Bano, N. Tonellotto, P. Cassarà and A. Gotta, "KafkaFed: Two-Tier Federated Learning Communication Architecture for Internet of Vehicles," 2022 IEEE International Conference on Pervasive Computing and Communications, Workshops and Affiliated Events (PerCom Workshops), 2022, pp. 515-520, doi: 10.1109/PerComWorkshops53856.2022.9767510. | ZENODO 
     
  • S. Bano, N. Tonellotto, P. Cassarà, A. Gotta, “FedTCS: Federated Learning with Time-based Client Selection to Optimize Edge Resources” Short Paper Proceedings of the First International Workshop on Artificial Intelligence in Beyond 5G and 6G Wireless Networks (AI6G 2022), Padova, Italy, July 21, 2022  | ZENODO 
     
  • S. Bano, A. Machumilane, L. Valerio, P. Cassará, A. Gotta, “Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks.” 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), 2022, pp. 165-170, doi: 10.1109/MELECON53508.2022.9843104. | ZENODO 
     
  • S. Bano., E. Carlini., P. Cassara', M. Coppola, P. Dazzi, A. Gotta, (2022, July). “A Novel Approach to Distributed Model Aggregation using Apache Kafka.” In Proceedings of the 2nd Workshop on Flexible Resource and Application Management on the Edge (pp. 33-36). doi: 10.1145/3526059.3533621  | ZENODO 
     
  • C. Gallicchio, “Reservoir Computing by Discretizing ODEs”, in Proceedings of the 2021 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021). DOI | ZENODO
     
  • V. De Caro et al., “AI-as-a-Service Toolkit for Human-Centered Intelligence in Autonomous Driving,” 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2022, pp. 91-93, doi: 10.1109/PerComWorkshops53856.2022.9767501 | ZENODO 
     
  • D. Bacciu, et al., “Towards Functional Safety Compliance of Recurrent Neural Networks.” CAIP 2021: Proceedings of the 1st International Conference on AI for People: Towards Sustainable AI, CAIP 2021, 20-24 November 2021, Bologna, Italy. European Alliance for Innovation, 2021 (DOI 10.4108/eai.20-11-2021.2314139) | ZENODO
     
  • Philipp Clement, Omar Veledar, Clemens Könczöl, Herbert Danzinger, Markus Posch, Arno Eichberger and Georg Macher "Enhancing Acceptance and Trust in Automated Driving through Virtual Experience on a Driving Simulator", MDPI, 2022 | MDPI link ZENODO
     
  • Davide Bacciu, Patrizio Dazzi and Alberto Gotta “Supporting Privacy Preservation by Distributed and Federated Learning on the Edge”, ERCIM News, No 127, 2021 | Link
     
  • H. Kavalionak, E.Carlini, P. Dazzi, L. Ferrucci, M. Mordacchini, M. Coppola, “Impact of Network Topology on the Convergence of Decentralized Federated Learning Systems”, 26th IEEE Symposium on Computers and Communications (ISCC 2021), September 5-8, 2021. | OpenPortal Link  ZENODO
     
  • Philipp Clement, Herbert Danzinger, Omar Veledar, Clemens Koenczoel, Georg Macher, Arno Eichberger, "Measuring trust in automated driving using a multi-level approach to human factors", Euromicro Conference on Digital System Design 2021 - Special Session: Intelligent Transportation Systems (ITS 2021), September 1-3, 2021 | ZENODO
     
  • D. Bacciu, D. Di Sarli, P. Faraji, C. Gallicchio, A. Micheli, “Federated Reservoir Computing Neural Networks”, International Joint Conference on Neural Networks (IJCNN 2021), July 18-22, 2021 | ZENODO
     
  • D. Bacciu, D. Di Sarli, C. Gallicchio, A. Micheli, N. Puccinelli, “Benchmarking Reservoir and Recurrent Neural Networks for Human State and Activity Recognition”, International Work-Conference on Artificial Neural Networks (IWANN 2021), June 16-18, 2021 | ZENODO
     
  • A. Cossu, D. Bacciu, A. Carta, C. Gallicchio, V. Lomonaco, “Continual Learning with Echo State Networks”, the 29th European Symposium on Artificial Neural Networks (ESANN 2021), 6-8 October 2021 | ZENODO
     
  • Claudio Gallicchio, Alessio Micheli, Luca Silvestri, “Phase Transition Adaptation”, International Joint Conference on Neural Networks (IJCNN 2021), July 18-22, 2021 | ZENODO
     
  • M. Dzambic, C. Kreuzberger, O. Veledar and G. Macher, “A Rapid Prototyping System, Intelligent Watchdog and Gateway Tool for Automotive Applications”, The 7th International Workshop on Automotive System/Software Architectures, (WASA2021), March 22-26, 2021 | ZENODO
     
  • J. Valtl, J. Mendez, M. Pegalajar and V. Issakov, “Autonomous Platform based on Small-Scale Car for Versatile Data Collection and Algorithm Verification”, 25th International Conference on Pattern Recognition, Milano, Italy, 2021 | ZENODO
     
  • K. Giorgas, I. Varlamis, “Online Federated Learning with Imbalanced Class Distribution”, Panhellenic Conference on Informatics, Nov. 2020  | ZENODO
     
  • D. Di Sarli, C. Gallicchio and A. Micheli, "Gated Echo State Networks: a preliminary study," 2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA), Novi Sad, Serbia, 2020 | ZENODO
     
  • C. Gallicchio, “Sparsity in Reservoir Computing Neural Networks”, September 11, 2020 DOI | ZENODO
  • Chronis C., Tserpes K., Varlamis I., «Autonomous Vehicle Systems in Intelligent Interconnected Transportation Networks», July 2023, ZENODO
     
  • Saira Bano; Nicola Tonellotto; Pietro Cassara; Alberto Gotta, «Artificial intelligence of things at the edge: Scalable and efficient distributed learning for massive scenarios», April 2023, ZENODO
     
  • Jakob Valtl; Vadim Issakov, «Universal Adversarial Attacks», October 2022, DOI
     
  • C. Davalas, D. Michail, C. Diou, I. Varlamis, K. Tserpes, (2022). “Computationally Efficient Rehearsal for Online Continual Learning.” Image Analysis and Processing – ICIAP 2022. Lecture Notes in Computer Science, vol 13233. Springer, Cham. | ZENODO
     
  • Nicola Tonellotto, Alberto Gotta, Franco Maria Nardini, Daniele Gadler, Fabrizio Silvestri, “Neural network quantization in federated learning at the edge”, Information Sciences, vol. 575, pp. 417-436, 2021 | ZENODO 

  • P. Cassará, A. Gotta, L. Valerio, “Federated Feature Selection for Cyber-Physical Systems of Systems.” IEEE Transactions on Vehicular Technology, 2022. DOI: 10.1109/TVT.2022.3178612  | ZENODO

  • C. Davalas, D. Michail, C. Diou, I. Varlamis, K. Tserpes, (2022). “Computationally Efficient Rehearsal for Online Continual Learning.” Image Analysis and Processing – ICIAP 2022. Lecture Notes in Computer Science, vol 13233. Springer, Cham. | ZENODO

  • C. Gallicchio, A. Micheli, “Architectural richness in deep reservoir computing”. Neural Comput & Applic (2022). DOI | ZENODO

  • D. Di Sarli, C. Gallicchio, A. Micheli, “On the effectiveness of Gated Echo State Networks for data exhibiting long-term dependencies.” Computer Science and Information Systems (2022) Volume 19, Issue 1, Pages: 379-396, DOI | ZENODO

  • A. Cossu, G. Graffieti, L. Pellegrini, D. Maltoni, D. Bacciu, A. Carta, V. Lomonaco, (2022). “Is Class-Incremental Enough for Continual Learning?” Frontiers in Artificial Intelligence, 5. | ZENODO

  • G. Merlin, V. Lomonaco, A. Cossu, A. Carta, D. Bacciu, (2022). “Practical Recommendations for Replay-Based Continual Learning Methods.” In: Mazzeo, P.L., Frontoni, E., Sclaroff, S., Distante, C. (eds) Image Analysis and Processing. ICIAP 2022 Workshops. Lecture Notes in Computer Science, vol 13374. Springer, Cham. DOI | ZENODO
  • A. Carta, A. Cossu, F. Errica, D. Bacciu, (2022). “Catastrophic Forgetting in Deep Graph Networks: A Graph Classification Benchmark.” Frontiers in Artificial Intelligence, 5. | ZENODO
     
  • Dobaj J., Macher G., Ekert D., Riel A., «Towards a security-driven automotive development lifecycle», November 2021, Link

  • D. Bacciu et al. “TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence”, Proceedings of the 2021 IEEE International Conference on Omni-layer Intelligent systems (IEEE COINS 2021), August 23-25, 2021 | ZENODO
     
  • J.Dobaj, D. Ekert, J. Stolfa, S. Stolfa, G. Macher, R. Messnarz “Cybersecurity Threat Analysis, Risk Assessment and Design Patterns for Automotive Networked Embedded Systems: A Case Study” at Journal of Universal Computer Science, 27(8), August 2021. | OnlineLink
     
  • Gabriele Mencagli, Massimo Torquati, Andrea Cardaci, Alessandra Fais, Luca Rinaldi, Marco Danelutto, "WindFlow: High-Speed Continuous Stream Processing with Parallel Building Blocks", IEEE Transactions on Parallel and Distributed Systems, vol. 32, no .11, 2021 | ZENODO
     
  • A. Cossu, A. Carta, V. Lomonaco, D. Bacciu, “Continual Learning for recurrent neural networks: An empirical evaluation”, Neural Networks, vol. 143, pp. 607-627, 2021 | ZENODO
     
  • D. Bacciu, G. Bertoncini, and D. Morelli, “Topographic mapping for quality inspection and intelligent filtering of smart-bracelet data” Neural Computing Applications, 2021 | ZENODO
     
  • A. Valenti, M. Barsotti, D. Bacciu and L. Ascari, “A Deep Classifier for Upper-Limbs Motor Anticipation Tasks in an Online BCI Setting”, Bioengineering, 8, 21, 2021 | ZENODO
     
  • M. V. Bordin, D. Griebler, G. Mencagli, C. F. R. Geyer and L. G. L. Fernandes, "DSPBench: A Suite of Benchmark Applications for Distributed Data Stream Processing Systems," IEEE Access, vol. 8, pp. 222900-222917, 2020 | ZENODO