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 ...

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...

New research shows that AI language models can develop a mathematical “understanding” that differentiates between events that are commonplace, improbable, impossible or just plain nonsense. PROVIDENCE ...

As AI becomes a daily work tool, the real risk may not be losing our intelligence—but losing confidence in our own thinking. New research suggests the difference comes down to how actively we engage ...