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F. Casado

3 papers hereh-index 9560 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG3

identity via Semantic Scholar / OpenAlex

most citedConcept drift detection and adaptation for federated and continual learning

81 citations · 87 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2021

Non-IID data and Continual Learning processes in Federated Learning: A long road ahead

Marcos F. Criado, Fernando E. Casado, Roberto Iglesias +2

Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. This dec…

cs.LG2021★ 81 cited

Concept drift detection and adaptation for federated and continual learning

Fernando E. Casado, Dylan Lema, Marcos F. Criado +3

Smart devices, such as smartphones, wearables, robots, and others, can collect vast amounts of data from their environment. This data is suitable for training machine learning mode…

cs.LG2020★ 6 cited

Federated and continual learning for classification tasks in a society of devices

Fernando E. Casado, Dylan Lema, Roberto Iglesias +2

Today we live in a context in which devices are increasingly interconnected and sensorized and are almost ubiquitous. Deep learning has become in recent years a popular way to extr…

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