Abstract Current evaluations of Continual Learning (CL) methods typically assume that there
is no constraint on training time and computation. This is an unrealistic assumption for any …

Modern machine learning pipelines are limited due to data availability, storage quotas,
privacy regulations, and expensive annotation processes. These constraints make it difficult …

In recent years, online distillation has emerged as a powerful technique for adapting real-
time deep neural networks on the fly using a slow, but accurate teacher model. However, a …

Online Class-Incremental (OCI) learning has sparked new approaches to expand the
previously trained model knowledge from sequentially arriving data streams with new …

The technique of online distillation has become increasingly popular in adapting real-time
deep neural networks using a slow and accurate teacher model. However, one of the most …

Los seres humanos aprenden continuamente nuevas actividades con pocos ejemplos sin
olvidar las aprendidas previamente, aprovechando la información multimodal …