3 papers
Beyond Backbone Backpropagation: A Decoupled Strategy for Efficient Transfer Learning
Daniel Vila-Cruz, Laura Morán-Fernández, Verónica Bolón-Canedo
Deep learning models achieve state-of-the-art image classification but face deployment challenges due to computational costs and energy demands. We propose a lightweight training s…
HydraCIL: Decoupled Class-Incremental Learning through Prototype-Guided Multi-Head Classifiers
Daniel Vila-Cruz, Laura Morán-Fernández, Verónica Bolón-Canedo
We present HydraCIL, a decoupled continual learning model based on prototype-guided multi-head classifiers, targeting sustainable deployment in embedded and resource-constrained en…
Closing the Alignment-Maturity Gap in Federated Prototype Learning
Mario Casado-Diez, Alejandro Dopico-Castro, Verónica Bolón-Canedo +1
Learning discriminative visual representations from distributed, heterogeneous data is a fundamental challenge in Federated Learning (FL). Prototype-based methods address statistic…