Federatedscope-llm: A comprehensive package for fine-tuning large language models in federated learning
Large language models (LLMs) have demonstrated great capabilities in various natural
language understanding and generation tasks. These pre-trained LLMs can be further …
language understanding and generation tasks. These pre-trained LLMs can be further …
Survey of federated learning models for spatial-temporal mobility applications
Federated learning involves training statistical models over edge devices such as mobile
phones such that the training data is kept local. Federated Learning (FL) can serve as an …
phones such that the training data is kept local. Federated Learning (FL) can serve as an …
Cross-silo federated learning with record-level personalized differential privacy
Federated learning (FL) enhanced by differential privacy has emerged as a popular
approach to better safeguard the privacy of client-side data by protecting clients' …
approach to better safeguard the privacy of client-side data by protecting clients' …
A multifaceted survey on federated learning: Fundamentals, paradigm shifts, practical issues, recent developments, partnerships, trade-offs, trustworthiness, and ways …
A Majeed, SO Hwang - IEEE Access, 2024 - ieeexplore.ieee.org
Federated learning (FL) is considered a de facto standard for privacy preservation in AI
environments because it does not require data to be aggregated in some central place to …
environments because it does not require data to be aggregated in some central place to …
Towards Context-Aware Federated Learning Assessment: A Reality Check
Federated learning (FL) enabled creating models that are competitive to centralized
machine learning models, without compromising user privacy. Participating FL clients train …
machine learning models, without compromising user privacy. Participating FL clients train …