Federated Learning (FL) has emerged as a solution for distributed systems that allow clients
to train models on their data and only share models instead of local data. Generative Models …

The ever-growing Internet of Things (IoT) connections drive a new type of organization, the
intelligent enterprise. In intelligent enterprises, machine learning-based models are adopted …

This work addresses a key limitation in current federated learning approaches, which
predominantly focus on homogeneous tasks, neglecting the task diversity on local devices …

In the field of federated learning, addressing non-independent and identically distributed
(non-iid) data remains a quintessential challenge for improving global model performance …

Federated learning enables collaborative training across various clients without data
exposure. However, data heterogeneity among clients may degrade system performance …

Federated Learning (FL) is a distributed machine learning paradigm that enables the
training of models across numerous clients or organizations without requiring the transfer of …