Abstract: Federated Learning (FL) is a privacy-preserving distributed Machine Learning (ML) technique. Hierarchical FL is a novel variant of FL applicable to networks with multiple layers. Instead of ...

Python gives you far more control, and the ecosystem is stacked with libraries that can replace most no-code platforms if you ...

We introduce DINOv2 SALAD, a Visual Place Recognition model that achieves state-of-the-art results on common benchmarks. We introduce two main contributions: Using a finetuned DINOv2 encoder to get ...

Abstract: Federated Learning (FL) is a collaborative machine learning (ML) framework that combines on-device training and server-based aggregation to train a common ML model among distributed agents.

to run the aecid-alert-aggregation with the default input files and configurations. To change the configuration, edit the aggregate_config.py file. The input files provided in this repository are ...