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Research Meeting 24144

Paradigms of ML: Links between human-, model- and data-centric learning

( Apr 01 – Apr 05, 2024 )

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  • Diego Botache (Universität Kassel, DE)
  • Kristina Dingel (Universität Kassel, DE)
  • David Meier (Helmholtz-Zentrum - Berlin, DE)



This workshop investigates the interconnections among three key paradigms in machine learning: human-centric, model-centric, and data-centric learning. The human-centric approach integrates domain expertise and human insights into the learning process, while model-centric learning emphasizes advanced algorithms and architectures. Data-centric learning prioritizes high-quality and diverse data. We want to explore the symbiotic relationships between these paradigms, revealing how human knowledge informs model development, how models influence data collection, and how data quality shapes model generalization abilities.

Copyright Diego Botache, Kristina Dingel, and David Meier

  • Artificial Intelligence
  • Machine Learning
  • Human-Computer Interaction