mlsanityData to 14 Oct 2026

Sustainable Artificial Intelligence through Continual Learning

arXiv 2111.09437 ↗First posted 17 Nov 2021cs.AI cs.LGcited by 4

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Abstract (arXiv)

The increasing attention on Artificial Intelligence (AI) regulation has led to the definition of a set of ethical principles grouped into the Sustainable AI framework. In this article, we identify Continual Learning, an active area of AI research, as a promising approach towards the design of systems compliant with the Sustainable AI principles. While Sustainable AI outlines general desiderata for ethical applications, Continual Learning provides means to put such desiderata into practice.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 6 of its 17 references that are in the map. First posted on arXiv 17 Nov 2021.

Builds on

6 of 17 references.

References · 6

  1. 2021Avalanche: an End-to-End Library for Continual Learningcited by 124
  2. 2018Continuous Learning in Single-Incremental-Task Scenarioscited by 109
  3. 2019Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and Challengescited by 93
  4. 2021Continual Learning for Recurrent Neural Networks: an Empirical Evaluationcited by 34
  5. 2015Continuous online sequence learning with an unsupervised neural network modelcited by 18
  6. 2020Online Continual Learning on Sequencescited by 14

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Cited by year

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

4 papers.

  1. 2022CL2R: Compatible Lifelong Learning Representationscited by 6
  2. 2022Contrastive Supervised Distillation for Continual Representation Learningcited by 3
  3. 2023Continual Learning with Deep Streaming Regularized Discriminant Analysiscited by 0
  4. 2024Recommendation of data-free class-incremental learning algorithms by simulating future datacited by 0