FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. (arXiv:2206.08671v1 [stat.ML])

Web: http://arxiv.org/abs/2206.08671

Modern deep learning systems are increasingly deployed in situations such as
personalization and federated learning where it is necessary to support i)
learning on small amounts of data, and ii) communication efficient distributed
training protocols. In this work we develop FiLM Transfer (FiT) which fulfills
these requirements in the image classification setting. FiT uses an
automatically configured Naive Bayes classifier on top of a fixed backbone that
has been pretrained on large image datasets. Parameter efficient FiLM layers
are used …

arxiv classification image learning ml personalized transfer transfer learning