A network of excellence for distributed, trustworthy, efficient and scalable AI at the Edge

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Pan-European Workshop on Edge AI technological trends and developments

Workshop of the NoE on future trends of edge AI

Workshop on industrial and investments priorities for successful AI at the Edge in Europe - Workshop Nr 1

Workshop for collaboration with PPP and industrial stakeholders

Seminars, workshop and events - Event Nr 1

Dissemination events, multiplier events

Roundtable on Edge AI functional and non-functional requirements

Expert workshop for requirements gathering and discussion

Workshops (co-organized with other pillars) - Workshop Nr 1

Two-day workshop for alignment with all pillars of the EU AI Lighthouse

Algorithms and methods prototype

First version of the edge AI algorithms

Call Announcement and Guide for Applicants - Call Nr 2

Open Call Package documents

Middleware prototype

First version of the middleware

Intermediate report and risk log - Report Nr 1

Updated report and log for risk prevention and mitigation (every 6 months)

Platform prototype

First version of the hardware platform solutions

dAIEDGE Communication, Dissemination and Exploitation plan

Plan of the project communication, dissemination and exploitation

Report on Edge AI functional and non-functional requirements

Comprehensive report on edge AI requirements

Call Announcement and Guide for Applicants - Call Nr 1

Open Call Package documents

Intermediate reports and risk log - Report Nr 3

Updated report and log for risk prevention and mitigation (every 6 months)

Evolutive infrastructure inventory - Report Nr 1

Inventory of existing infrastructure for edge AU

Quality assurance plan

Measures for ensuring quality

Risk management plan

Plan and measures for risk prevention and mitigation

Distributed network design

Design and architecture of the distributed network of frameworks

Intermediate reports and risk log - Report Nr 2

Updated report and log for risk prevention and mitigation (every 6 months)

Reference document on European AI Lighthouse implementation

Plans and recommendations organisation of the EU AI Lighthouse

Evolutive infrastructure inventory - Report Nr 2

Inventory of existing infrastructure for edge AU

dAIEDGE Communication, Dissemination and Exploitation plan - update Nr 1

First update of the dAIEDGE Communication, Dissemination and Exploitation plan

Report on Use Case definition, demonstration setup and validation plan

Complete and refined definition of the three use cases with evaluation plan

Final data management plan

Plan for management of data in the NoE and in the consortium - final version

Initial data management plan

Plan for management of data in the NoE and in the consortium - intial version

Pubblicazioni

Optimization strategies for neural network deployment on FPGA: An energy-efficient real-time face detection use case

Autori: Mhd Rashed Al Koutayni, Gerd Reis, Didier Stricker
Pubblicato in: Internet of Things, Numero 33, 2026, ISSN 2542-6605
Editore: Elsevier BV
DOI: 10.1016/J.IOT.2025.101676

SpikeFI: A Fault Injection Framework for Spiking Neural Networks

Autori: Theofilos Spyrou; Said Hamdioui; Haralampos-G. Stratigopoulos
Pubblicato in: CoRR, 2024, ISSN 2331-8422
Editore: arXiv
DOI: 10.5281/ZENODO.15401569

WRIT: Web Request Integrity and Attestation Against Malicious Browser Extensions

Autori: Giorgos Vasiliadis, Apostolos Karampelas, Alexandros Shevtsov, Panagiotis Papadopoulos, Sotiris Ioannidis, Alexandros Kapravelos
Pubblicato in: IEEE Transactions on Dependable and Secure Computing, Numero 21, 2024, ISSN 1545-5971
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TDSC.2023.3322516

Federated Learning for Collaborative Inference Systems: The case of early exit networks

Autori: Chuan Xu, Caelin Kaplan, Angelo Rodio, Tareq Si Salem, Giovanni Neglia
Pubblicato in: Performance Evaluation, Numero 171, 2026, ISSN 0166-5316
Editore: Elsevier BV
DOI: 10.1016/J.PEVA.2025.102538

Concealed Weapon Detection Using Thermal Cameras

Autori: Juan D. Muñoz, Jesus Ruiz-Santaquiteria, Oscar Deniz, Gloria Bueno
Pubblicato in: Journal of Imaging, Numero 11, 2025, ISSN 2313-433X
Editore: MDPI AG
DOI: 10.3390/JIMAGING11030072

A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication

Autori: Angelo Rodio, Giovanni Neglia, Zheng Chen, Erik G. Larsson
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 40, 2026, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V40I30.39705

Adversarial Examples Detection with Chaos-Based Multivariate Features

Autori: Harbinder Singh, Anibal Pedraza, Oscar Deniz, Gloria Bueno
Pubblicato in: International Journal of Machine Learning and Cybernetics, Numero 16, 2025, ISSN 1868-8071
Editore: Springer Science and Business Media LLC
DOI: 10.1007/S13042-025-02657-2

Neighbor Selection Strategies in the Wild for CDN/V2V WebRTC Live Streaming: Can we learn what a good neighbor is?

Autori: Ma, Zhejiayu; Giroire, Frédéric; Urvoy-Keller, Guillaume; Rouibia, Soufiane
Pubblicato in: 2022 IEEE 47th Conference on Local Computer Networks (LCN), 2022, ISSN 1872-7069
Editore: Elsevier
DOI: 10.1016/J.COMNET.2025.111783

Digital Sovereignty for Collaborative AI Engineering: A Survey

Autori: Venkata Satya Sai Ajay Daliparthi, Kurt Tutschku, Victor R. Kebande, Nurul Momen
Pubblicato in: IEEE Access, Numero 13, 2026, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/ACCESS.2025.3647085

A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses

Autori: Caelin Kaplan, Chuan Xu, Othmane Marfoq, Giovanni Neglia, Anderson Santana de Oliveira
Pubblicato in: Proceedings on Privacy Enhancing Technologies, Numero 2024, 2023, ISSN 2299-0984
Editore: Privacy Enhancing Technologies Symposium Advisory Board
DOI: 10.56553/popets-2024-0031

Low-Complexity online learning for caching

Autori: Damiano Carra, Giovanni Neglia, Xufeng Zhang
Pubblicato in: Computer Networks, Numero 273, 2025, ISSN 1389-1286
Editore: Elsevier BV
DOI: 10.1016/J.COMNET.2025.111743

Operator as a Service: A New Concept for Remote Supervision of Automated Manufacturing Lines

Autori: Marco Ojer, Sergio Valdés, Ander Garcia, Xabier Oregui, Iker Gastesi, Xiao Lin, Iñigo Mendizabal-Arrieta, Jairo R. Sanchez, Elena Lazkano
Pubblicato in: IEEE Access, Numero 13, 2025, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/ACCESS.2025.3574415

Detection of adversarial examples through chaos quantification in time-series analysis

Real-Time Edge Computing vs. GPU-Accelerated Pipelines for Low-Cost Microscopy Applications

Autori: Gloria Bueno, Lucia Sanchez-Vargas, Alberto Diaz-Maroto, Jesus Ruiz-Santaquiteria, Maria Blanco, Jesus Salido, Gabriel Cristobal
Pubblicato in: Electronics, Numero 14, 2025, ISSN 2079-9292
Editore: MDPI AG
DOI: 10.3390/ELECTRONICS14050930

Data Center Scheduling With Network Tasks

Autori: Giroire, Frédéric; Huin, N.; Tomassilli, Andrea; Pérennes, S.
Pubblicato in: IEEE Transactions on Networking, 2025, ISSN 2998-4157
Editore: IEEE
DOI: 10.1109/TON.2025.3578455

Autori: Jesus Ruiz-Santaquiteria, Juan D. Muñoz, Francisco J. Maigler, Oscar Deniz, Gloria Bueno
Pubblicato in: Data in Brief, Numero 52, 2024, ISSN 2352-3409
Editore: Elsevier BV
DOI: 10.1016/J.DIB.2024.110030

DLAS: A Conceptual Model for Across-Stack Deep Learning Acceleration

Autori: Perry Gibson, Jose Cano, Elliot Crowley, Amos Storkey, Michael O'Boyle
Pubblicato in: ACM Transactions on Architecture and Code Optimization, 2024, ISSN 1544-3566
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3688609

Embeddings hidden layers learning for neural network compression

Autori: Jia Cheng Hu, Roberto Cavicchioli, Alessandro Capotondi
Pubblicato in: Neural Networks, Numero 191, 2025, ISSN 0893-6080
Editore: Elsevier BV
DOI: 10.1016/J.NEUNET.2025.107794

Leveraging AutoEncoders and chaos theory to improve adversarial example detection

Autori: Anibal Pedraza, Oscar Deniz, Harbinder Singh, Gloria Bueno
Pubblicato in: Neural Computing and Applications, Numero 36, 2024, ISSN 0941-0643
Editore: Springer Science and Business Media LLC
DOI: 10.1007/S00521-024-10141-1

Exploiting Multiple Sequence Lengths in Fast End to End Training for Image Captioning

Autori: Hu, Jia Cheng; Cavicchioli, Roberto; Capotondi, Alessandro
Pubblicato in: 2023 IEEE International Conference on Big Data (BigData), 2023, ISSN 2998-4157
Editore: IEEE
DOI: 10.48550/ARXIV.2208.06551

Online Self-Supervised Learning for Accurate Pick Assembly Operation Optimization

Autori: Sergio Valdés, Marco Ojer, Xiao Lin
Pubblicato in: Robotics, Numero 14, 2025, ISSN 2218-6581
Editore: MDPI AG
DOI: 10.3390/ROBOTICS14010004

Fast Transciphering Via Batched And Reconfigurable LUT Evaluation

Autori: Leonard Schild, Aysajan Abidin, Bart Preneel
Pubblicato in: IACR Transactions on Cryptographic Hardware and Embedded Systems, Numero 2024, 2024, ISSN 2569-2925
Editore: Universitatsbibliothek der Ruhr-Universitat Bochum
DOI: 10.46586/tches.v2024.i4.205-230

ShareBERT: Embeddings Are Capable of Learning Hidden Layers

Autori: Jia Cheng Hu, Roberto Cavicchioli, Giulia Berardinelli, Alessandro Capotondi
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 38, 2024, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/aaai.v38i16.29781

Characterizing Natural Adversarial Examples Through Activation Map Analysis

Autori: Anibal Pedraza; Nerea Leon; Harbinder Singh; Oscar Deniz; Gloria Bueno
Pubblicato in: IET Image Processing, 2025, ISSN 1751-9667
Editore: Wiley
DOI: 10.1049/IPR2.70123

Trusted Yet Flexible: High-Level Runtimes for Secure ML Inference in TEEs

Autori: Nikolaos-Achilleas Steiakakis, Giorgos Vasiliadis
Pubblicato in: Journal of Cybersecurity and Privacy, Numero 6, 2026, ISSN 2624-800X
Editore: MDPI AG
DOI: 10.3390/JCP6010023

DeepGun: Deep Feature-Driven One-Class Classifier for Firearm Detection Using Visual Gun Features and Human Body Pose Estimation

Autori: Harbinder Singh; Oscar Deniz; Jesus Ruiz-Santaquiteria; Juan D. Muñoz; Gloria Bueno
Pubblicato in: Applied Sciences, 2025, ISSN 2076-3417
Editore: MDPI
DOI: 10.3390/APP15115830

MLOps for Edge AI: Satellite Sea Ice Detection Test Bed

Autori: Juan Odriozola, Giovanni Paolini, Markel Flores, Ander Garcia
Pubblicato in: Lecture Notes in Networks and Systems, Distributed Computing and Artificial Intelligence, Special Sessions II, 22nd International Conference, 2026
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-032-05748-8_38

Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning

Autori: Francesco Diana, André Nusser, Chuan Xu, Giovanni Neglia
Editore: ACM
DOI: 10.5555/3762387.3762431

When to forget? complexity trade-offs in machine unlearning

Autori: Martin Van Waerebeke, Marco Lorenzi, Giovanni Neglia, Kevin Scaman
Pubblicato in: ICML'25: Proceedings of the 42nd International Conference on Machine Learning
Editore: ACM
DOI: 10.5555/3780338.3782750

AnonyNoise: Anonymizing Event Data with Smart Noise to Outsmart Re-Identification and Preserve Privacy

Autori: Katharina Bendig, René Schuster, Nicole Thiemer, Karen Joisten, Didier Stricker
Pubblicato in: Proceedings of the Winter Conference on Applications of Computer Vision (WACV)
Editore: WACV
DOI: 10.48550/ARXIV.2411.16440

Exploring Adversarial Attacks on the MaSTer Truncation Protocol

Autori: Zbudila, Martin Abidin, Aysajan Preneel, Bart
Editore: ACM
DOI: 10.1145/3733102.3733119

Efficient Tiny Machine Learning for Human Activity Recognition on Low-Power Edge Devices

Autori: Vinamra Sharma, Danilo Pau, José Cano
Pubblicato in: 2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI), 2024
Editore: IEEE
DOI: 10.1109/RTSI61910.2024.10761203

einspace: Searching for Neural Architectures from Fundamental Operations

Autori: Linus Ericsson, Miguel Espinosa, Chenhongyi Yang, Antreas Antoniou, Amos Storkey, Shay Cohen, Steven McDonagh, Elliot Crowley
Pubblicato in: Advances in Neural Information Processing Systems 37, 2026
Editore: Neural Information Processing Systems Foundation, Inc. (NeurIPS)
DOI: 10.52202/079017-0061

Steerable Zero-Shot Neural Architecture Search for Efficient Edge Inference

Autori: Simon Narduzzi, Rémy Vuagniaux, Kishan Sharma, Shih-Chii Liu, L. Andrea Dunbar
Pubblicato in: 2025 IEEE International Symposium on Circuits and Systems (ISCAS), 2025, ISSN 2158-1525
Editore: IEEE
DOI: 10.1109/ISCAS56072.2025.11044278

On the Sparsity of the Strong Lottery Ticket Hypothesis

Autori: Emanuele Natale , Davide Ferre’ , Giordano Giambartolomei , Frédéric Giroire, Frederik Mallmann-Trenn
Editore: HAL science ouverte

Enhancing AI Benchmarking in dAIEdge-VLab with Blockchain Technology

Autori: Raúl López-Blanco, Diego Valdeolmillos, Maïck Huguenin, Baptiste Dupertuis, Gregoire Rebstein, Margaux Divernois, Nuria Pazos Escudero
Pubblicato in: Lecture Notes in Networks and Systems, Distributed Computing and Artificial Intelligence, Special Sessions II, 22nd International Conference, 2026
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-032-05748-8_46

Scaling-up Memristor Monte Carlo with magnetic domain-wall physics

Autori: Dalgaty, Thomas; Yamada, Shogo; Molnos, Anca; Kawasaki, Eiji; Mesquida, Thomas; Rummens, François; Shibata, Tatsuo; Urakawa, Yukihiro; Terasaki, Yukio; Sasaki, Tomoyuki; Duranton, Marc
Pubblicato in: CoRR, 2023
Editore: arXiv
DOI: 10.48550/ARXIV.2312.02771

PELS: A Lightweight and Flexible Peripheral Event Linking System for Ultra-Low Power IoT Processors

Autori: Alessandro Ottaviano, Robert Balas, Philippe Sauter, Manuel Eggimann, Luca Benini
Pubblicato in: 2024 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE), 2024
Editore: IEEE
DOI: 10.23919/DATE58400.2024.10546868

FedStale: leveraging Stale Updates in Federated Learning

Autori: Angelo Rodio, Giovanni Neglia
Pubblicato in: Frontiers in Artificial Intelligence and Applications, ECAI 2024, 2024
Editore: IOS Press
DOI: 10.3233/FAIA240849

LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots

Autori: Dongge Han, Trevor McInroe, Adam Jelley, Stefano V. Albrecht, Peter Bell, Amos Storkey
Pubblicato in: Proceedings of the 31st International Conference on Computational Linguistics, 2025
Editore: Association for Computational Linguistics (ACL)

Toward Scalable XR Interfaces for Human-Robot Collaboration with AMRs: Localization and Co-carrying via Synthetic Data

Autori: Eva Almansa, Xiao Lin, Iñigo Mendizabal-Arrieta, Sara García
Pubblicato in: Lecture Notes in Networks and Systems, Distributed Computing and Artificial Intelligence, 22nd International Conference, 2026
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-032-04160-9

Input-Triggered Hardware Trojan Attack on Spiking Neural Networks

Autori: Spyridon Raptis, Paul Kling, Ioannis Kaskampas, Ihsen Alouani, Haralampos-G. Stratigopoulos
Pubblicato in: 2025 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2025
Editore: IEEE
DOI: 10.1109/HOST64725.2025.11050044

Distributed Inference with Minimal Off-Chip Traffic for Transformers on Low-Power MCUs

Autori: Severin Bochem, Victor J.B. Jung, Arpan Suravi Prasad, Francesco Conti, Luca Benini
Pubblicato in: 2025 Design, Automation &amp; Test in Europe Conference (DATE), 2025
Editore: IEEE
DOI: 10.23919/DATE64628.2025.10992712

Attribute Inference Attacks for Federated Regression Tasks

Autori: Francesco Diana, Othmane Marfoq, Chuan Xu, Giovanni Neglia, Frédéric Giroire, Eoin Thomas
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 39, 2025, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I15.33787

STDP-Trained Spiking Neural Network Reliability Assessment Through Fault Injections

Autori: Zalfa Jouni, Haralampos-G. Stratigopoulos
Pubblicato in: 2025 IEEE 31st International Symposium on On-Line Testing and Robust System Design (IOLTS), 2025
Editore: IEEE
DOI: 10.1109/IOLTS65288.2025.11116934

YCB-Ev 1.1: Event-vision dataset for 6DoF object pose estimation

Autori: Pavel Rojtberg, Thomas Pöllabauer
Pubblicato in: European Conference on Computer Vision
Editore: Springer

Quadrilatero: A RISC-V programmable matrix coprocessor for low-power edge applications

Autori: Danilo Cammarata, Matteo Perotti, Marco Bertuletti, Angelo Garofalo, Pasquale Davide Schiavone, David Atienza, Luca Benini
Pubblicato in: Proceedings of the 22nd ACM International Conference on Computing Frontiers: Workshops and Special Sessions, 2025
Editore: ACM
DOI: 10.1145/3706594.3726978

Biases in Edge Language Models: Detection, Analysis, and Mitigation

Autori: Vinamra Sharma, Danilo Pau, José Cano
Pubblicato in: EDGE AI Research Symposium (EDGEAI) Austin 2025
Editore: arXiv

Input-Specific and Universal Adversarial Attack Generation for Spiking Neural Networks in the Spiking Domain

Autori: Spyridon Raptis, Haralampos-G. Stratigopoulos
Pubblicato in: 2025 International Joint Conference on Neural Networks (IJCNN), 2025
Editore: IEEE
DOI: 10.1109/IJCNN64981.2025.11228887

IFIP Networking 2025 Conference

Autori: Xufeng Zhang, Sara Alouf, Giovanni Neglia
Editore: IFIP Networking 2025

Scheduling with Fully Compressible Tasks: Application to Deep Learning Inference with Neural Network Compression

Autori: Tiago Da Silva Barros, Frédéric Giroire, Ramon Aparicio-Pardo, Stéphane Pérennes, Emanuele Natale
Pubblicato in: 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2024
Editore: IEEE
DOI: 10.1109/CCGrid59990.2024.00045

Weapon Detection Using PTZ Cameras

Autori: Juan Daniel Muñoz, Jesus Ruiz-Santaquiteria, Oscar Deniz, Gloria Bueno
Pubblicato in: Communications in Computer and Information Science, Robotics, Computer Vision and Intelligent Systems, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-59057-3_7

Scalable Decentralized Algorithms for Online Personalized Mean Estimation

Autori: Franco Galante, Giovanni Neglia, Emilio Leonardi
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 39, 2025, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I16.33835

Transferrable Surrogates in Expressive Neural Architecture Search Spaces

Autori: Shiwen Qin, Gabriela Kadlecová, Martin Pilát, Shay B. Cohen, Roman Neruda, Elliot J. Crowley, Jovita Lukasik, Linus Ericsson
Pubblicato in: Proceedings of Machine Learning Research, 2025
Editore: PMLR
DOI: 10.48550/ARXIV.2504.12971

STEER: Software Toolkit for Edge Efficient Retraining

Autori: Konstantina Orfanou, Christos Kozanitis
Pubblicato in: Proceedings of the Sixth European Workshop on Machine Learning and Systems, 2026
Editore: ACM
DOI: 10.1145/3805621.3807620

Multi-Partner Project: dAIEDGE - A Network of Excellence for Distributed, Trustworthy, Efficient and Scalable AI at the Edge

Autori: Pagani, A., Cano, J., Stratigopoulos, H. G., Abidin, A., Al Koutayni, M. R., Benini, L., ... & Wiehle, S.
Pubblicato in: Design, Automation and Test in Europe Conference
Editore: IEEE

Learning from Wrong Predictions in Low-Resource Neural Machine Translation

Autori: Hu, Jia Cheng; Cavicchioli, Roberto; Berardinelli, Giulia; Capotondi, Alessandro
DOI: 10.5281/ZENODO.15394124

Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models

Autori: Nicolas Baumann, Cheng Hu, Paviththiren Sivasothilingam, Haotong Qin, Lei Xie, Michele Magno, Luca Benini
Editore: Robotics: Science and Systems Proceedings
DOI: 10.48550/ARXIV.2504.11514

Exploiting Multiple Sequence Lengths in Fast End to End Training for Image Captioning

Autori: Jia Cheng Hu, Roberto Cavicchioli, Alessandro Capotondi
Pubblicato in: 2023 IEEE International Conference on Big Data (BigData), 2024
Editore: IEEE
DOI: 10.1109/BIGDATA59044.2023.10386812

FedBed: Benchmarking Federated Learning over Virtualized Edge Testbeds

Autori: Symeonides, M., Nikolaidis, F., Trihinas, D., Pallis, G., Dikaiakos, M. D., & Bilas, A.
Pubblicato in: UCC '23: Proceedings of the IEEE/ACM 16th International Conference on Utility and Cloud Computing
Editore: Association for Computing MachineryNew YorkNYUnited States
DOI: 10.1145/3603166.363213

The Bidirectional Awareness Induction in Autoregressive Sequence-To-Sequence Models

Autori: Jia Cheng Hu
Pubblicato in: 31th International Conference on Neural Information Processing (ICONIP) abstracts, 2025
Editore: Tuwhera
DOI: 10.24135/ICONIP25

BatDeck: Advancing Nano-Drone Navigation with Low-Power Ultrasound-Based Obstacle Avoidance

Autori: Hanna Müller, Victor Kartsch, Michele Magno, Luca Benini
Pubblicato in: 2024 IEEE Sensors Applications Symposium (SAS), 2024
Editore: IEEE
DOI: 10.1109/SAS60918.2024.10636518

Hardware-Accelerated Event-Graph Neural Networks for Low-Latency Time-Series Classification on SoC FPGA

Autori: Hiroshi Nakano, Krzysztof Blachut, Kamil Jeziorek, Piotr Wzorek, Manon Dampfhoffer, Thomas Mesquida, Hiroaki Nishi, Tomasz Kryjak, Thomas Dalgaty
Pubblicato in: Lecture Notes in Computer Science, Applied Reconfigurable Computing. Architectures, Tools, and Applications, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-87995-1

Minimum Time Maximum Fault Coverage Testing of Spiking Neural Networks

Autori: Spyridon Raptis, Haralampos-G. Stratigopoulos
Pubblicato in: 2025 Design, Automation &amp; Test in Europe Conference (DATE), 2025
Editore: IEEE
DOI: 10.23919/DATE64628.2025.10993048

On the Fault Sensitivity of Natural Language Embeddings Computation

Autori: S. Sapkal, U. Zahid, G. Gambardella, H. -G. Stratigopoulos and B. Clerkin
Pubblicato in: 2025 IEEE European Test Symposium (ETS)
Editore: IEEE
DOI: 10.1109/ETS63895.2025.11049603

Work in Progress: Linear Transformers for TinyML

Autori: Moritz Scherer, Cristian Cioflan, Michele Magno, Luca Benini
Pubblicato in: 2024 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE), 2024
Editore: IEEE
DOI: 10.23919/DATE58400.2024.10546828

Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm

Autori: Batiste Le Bars , Aurélien Bellet , Marc Tommasi , Kevin Scaman , Giovanni Neglia
Editore: HAL science ouverte

AAS to support the Operator as a Service vision

Autori: Ander Garcia, Xabier Oregui, Marco Ojer, Sergio Valdés, Jairo R. Sánchez, Iñigo Mendizabal
Pubblicato in: 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA), 2025
Editore: IEEE
DOI: 10.1109/ETFA65518.2025.11205634

Link inference attacks in vertical federated graph learning

Autori: O. Zari, C. Xu, J. Parra-Arnau, A. Ünsal, M. Önen
Editore: IEEE

Green Federated Learning via Carbon-Aware Client and Time Slot Scheduling

Autori: Daniel Richards Arputharaj, Charlotte Rodriguez, Angelo Rodio, Giovanni Neglia
Pubblicato in: 2025 33rd International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), 2026
Editore: IEEE
DOI: 10.1109/MASCOTS67699.2025.11283314

Scheduling Machine Learning Compressible Inference Tasks with Limited Energy Budget

Autori: Tiago Da Silva Barros, Davide Ferre, Frederic Giroire, Ramon Aparicio-Pardo, Stephane Perennes
Pubblicato in: Proceedings of the 53rd International Conference on Parallel Processing, 2024
Editore: ACM
DOI: 10.1145/3673038.3673106

F-BFQ: Flexible Block-Floating Point Quantization Accelerator for LLMs

Autori: Jude Haris, José Cano
Pubblicato in: Workshop on New Approaches for Addressing the Computing Requirements of LLMs and GNNs (LG-ARC) @ ISCA 2025
Editore: arXiv

Satellite on-board processing of synthetic aperture radar data for rapid delivery of latency sensitive maritime information products

Autori: Dominik Günzel, Srikanth Mandapati
Pubblicato in: Active and Passive Remote Sensing of Oceans, Seas, and Lakes, 2025
Editore: SPIE
DOI: 10.1117/12.3040646

InferONNX: Practical and Privacy-Preserving Machine Learning Inference Using Trusted Execution Environments

Autori: Konstantina Papafragkaki, Giorgos Vasiliadis
Pubblicato in: Lecture Notes in Computer Science, Detection of Intrusions and Malware, and Vulnerability Assessment, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-97623-0_2

Event-based Audio Prediction with Spectro-Temporal Event-Graphs

Autori: Lars Rafeldt, Thomas Mesquida, Hiroshi Nakano, Manon Dampfhoffer, Filippo Moro, Pascal Vivet, Melika Payvand, Thomas Dalgaty
Pubblicato in: 2025 IEEE International Symposium on Circuits and Systems (ISCAS), 2025
Editore: IEEE
DOI: 10.1109/ISCAS56072.2025.11043865

Evaluating Ascon in Secure Multi-Party Computation using Reverse Multiplication-Friendly Embeddings

Autori: Peter Schwarz, Erik Pohle, Aysajan Abidin, Bart Preneel
Pubblicato in: Proceedings of the 24th Workshop on Privacy in the Electronic Society, 2026
Editore: ACM
DOI: 10.1145/3733802.3764050

FedLoRa: IoT Spectrum Sensing Through Fast and Energy-Efficient Federated Learning in LoRa Networks

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