Abstract: Federated learning is an emerging machine learning paradigm that effectively alleviates the data silo problem by distributing the model training process to multiple data holders. However, ...
Abstract: Open-vocabulary multi-label classification aims to identify the labels for all significant objects of interest in the scene, including new objects unseen in the training set. Recent studies ...