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[TEACHING] A computing toolkit for building efficient autonomous applications leveraging humanistic intelligence (871385)
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24 Research products, page 1 of 3

  • Publications

10
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  • Open Access
    Authors: 
    Philipp Clement; Omar Veledar; Clemens Könczöl; Herbert Danzinger; Markus Posch; Arno Eichberger; Georg Macher;
    Publisher: MDPI AG
    Country: Austria
    Project: EC | TEACHING (871385), EC | TrustVehicle (723324)

    As vehicle driving evolves from human-controlled to autonomous, human–machine interaction ensures intuitive usage as well as the feedback from vehicle occupants to the machine for optimising controls. The feedback also improves understanding of the user satisfaction wit...

  • Publication . Conference object . 2021
    Authors: 
    Dimitris Palyvos-Giannas; Gabriele Mencagli; Marina Papatriantafilou; Vincenzo Gulisano;
    Publisher: ACM
    Project: EC | TEACHING (871385)

    Data streaming applications in Cyber-Physical Systems enable high-throughput, low-latency transformations of raw data into value. The performance of such applications, run by Stream Processing Engines (SPEs), can be boosted through custom CPU scheduling. Previous schedu...

  • Open Access
    Authors: 
    Gabriele Mencagli; Massimo Torquati; Andrea Cardaci; Alessandra Fais; Luca Rinaldi; Marco Danelutto;
    Publisher: Zenodo
    Project: EC | TEACHING (871385)

    Nowadays, we are witnessing the diffusion of Stream Processing Systems (SPSs) able to analyze data streams in near realtime. Traditional SPSs like Storm and Flink target distributed clusters and adopt the continuous streaming model , where inputs are processed as soon a...

  • Open Access
    Authors: 
    Valtl, Jakob; Issakov Vadim;
    Publisher: Zenodo
    Project: EC | TEACHING (871385)

    Autonomous driving is a highly complex task, which involves the use of numerous sensors and various algorithms. Testing of algorithms is difficult and therefore mostly done in simulations. Radar technology will play a key part due to various advantages. In this paper we...

  • Open Access English
    Authors: 
    Cassarà, Pietro; Gotta, Alberto; Valerio, Lorenzo;
    Project: EC | HumanE-AI-Net (952026), EC | SoBigData-PlusPlus (871042), EC | MARVEL (957337), EC | TEACHING (871385)

    Autonomous vehicles (AVs) generate a massive amount of multi-modal data that once collected and processed through Machine Learning algorithms, enable AI-based services at the Edge. In fact, not all these data contain valuable, and informative content but only a subset o...

  • Open Access
    Authors: 
    Philipp Clement; Herbert Danzinger; Omar Veledar; Clemens Konczol; Georg Macher; Arno Eichberger;
    Publisher: Zenodo
    Project: EC | TEACHING (871385), EC | TrustVehicle (723324)

    As the driving is shifting towards automation, the maximization of related benefits would profit from improved user acceptance of the new technology. Studies suggest a strong connection between acceptance and trust in technical solutions. We investigate the improvement ...

  • Open Access
    Authors: 
    Kavalionak H.; Carlini E.; Dazzi P.; Ferrucci L.; Mordacchini M.; Coppola M.;
    Publisher: IEEE
    Country: Italy
    Project: EC | TEACHING (871385)

    Federated learning is a popular framework that enables harvesting edge resources' computational power to train a machine learning model distributively. However, it is not always feasible or profitable to have a centralized server that controls and synchronizes the train...

  • Open Access
    Authors: 
    Davide Bacciu; Siranush Akarmazyan; Eric Armengaud; Manlio Bacco; George Bravos; Calogero Calandra; Emanuele Carlini; Antonio Carta; Pietro Cassara; Massimo Coppola; +25 more
    Publisher: Zenodo
    Country: Italy
    Project: EC | TEACHING (871385)

    This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud continuum. TEACHING ...

  • Publication . Conference object . 2021
    Open Access
    Authors: 
    Davide Bacciu; Daniele Di Sarli; Pouria Faraji; Claudio Gallicchio; Alessio Micheli;
    Publisher: Zenodo
    Country: Italy
    Project: EC | TEACHING (871385)

    A critical aspect in Federated Learning is the aggregation strategy for the combination of multiple models, trained on the edge, into a single model that incorporates all the knowledge in the federation. Common Federated Learning approaches for Recurrent Neural Networks...

  • Publication . Preprint . Conference object . 2021
    Open Access English
    Authors: 
    Claudio Gallicchio; Alessio Micheli; Luca Silvestri;
    Publisher: Institute of Electrical and Electronics Engineers Inc.
    Country: Italy
    Project: EC | TEACHING (871385)

    Artificial Recurrent Neural Networks are a powerful information processing abstraction, and Reservoir Computing provides an efficient strategy to build robust implementations by projecting external inputs into high dimensional dynamical system trajectories. In this pape...