mlsanityData to 14 Oct 2026

TEACHING -- Trustworthy autonomous cyber-physical applications through human-centred intelligence

arXiv 2107.06543 ↗First posted 14 Jul 2021cs.AI cs.LGcited by 4

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Abstract (arXiv)

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 puts forward a human-centred vision leveraging the physiological, emotional, and cognitive state of the users as a driver for the adaptation and optimization of the autonomous applications. It does so by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security and privacy preservation. The paper discusses the main concepts of the TEACHING approach and singles out the main AI-related research challenges associated with it. Further, we provide a discussion of the design choices for the TEACHING system to tackle the aforementioned challenges

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 6 of its 26 references that are in the map. First posted on arXiv 14 Jul 2021.

Builds on

6 of 26 references.

References · 6

  1. 2017Wild Patterns: Ten Years After the Rise of Adversarial Machine Learningcited by 414
  2. 2013Zero-Shot Learning Through Cross-Modal Transfercited by 237
  3. 2019A Gentle Introduction to Deep Learning for Graphscited by 108
  4. 2021Continual Learning for Recurrent Neural Networks: an Empirical Evaluationcited by 34
  5. 2020Continual Learning with Gated Incremental Memories for sequential data processingcited by 12
  6. 2021Continual Learning with Echo State Networkscited by 8

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Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 1.

4 papers.

  1. 2021Federated Feature Selection for Cyber-Physical Systems of Systemscited by 11
  2. 2022AI-as-a-Service Toolkit for Human-Centered Intelligence in Autonomous Drivingcited by 1
  3. 2022Federated Adaptation of Reservoirs via Intrinsic Plasticitycited by 0
  4. 2024Graph Neural Networks and Reinforcement Learning for Proactive Application Image Placementcited by 0