Results 91 to 100 of about 31,140,529 (283)

Pretraining Client Selection Algorithm Based on a Data Distribution Evaluation Model in Federated Learning

IEEE Access
Federated Learning (FL) allows task initiators (servers) to utilize data from task participants (clients) to train machine learning models while protecting data privacy.
Chang Xu, Hong Liu, Kexin Li, Wanglei Feng, Wei Qi   +4 more
doaj   +1 more source

Sustainable and Resilient Supply Networks: Digitalisation, Regulation and Climate Vulnerability in a Global Context

Business Strategy and the Environment, EarlyView.
ABSTRACT The growing frequency of global crises has intensified concerns regarding climate vulnerability and the resilience of global production systems. This study examines the heterogeneous effects of supply chain development and supply chain digitalisation on climate vulnerability across countries, while accounting for institutional and investment ...
Ziwei Li, Zhi Zhan, Kingsley Imandojemu, Romanus Osabohien, Damilola Felix Eluyela   +4 more
wiley   +1 more source

Do Commodity Prices and Energy Markets Drive Asymmetric Volatility in Biodiversity Finance?

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines symmetric and asymmetric volatility spillovers among biodiversity finance, commodity prices, and energy markets using daily data from 2019 to 2025. We apply the Diebold–Yilmaz time–domain connectedness model, Baruník–Křehlík frequency–domain decomposition, and an asymmetric spillover framework.
Ijaz Younis, Maqsood Ahmad, Himani Gupta, Kun Su, Waheed Ullah Shah   +4 more
wiley   +1 more source

Analysis and Improvement of Entropy Estimators in NIST SP 800-90B for Non-IID Entropy Sources

IACR Transactions on Symmetric Cryptology, 2017
Random number generators (RNGs) are essential for cryptographic applications. In most practical applications, the randomness of RNGs is provided by entropy sources.
Shuangyi Zhu, Yuan Ma, Tianyu Chen, Jingqiang Lin, Jiwu Jing   +4 more
doaj   +1 more source

How Do Energy Prices, Financial Conditions, and ESG‐Related Uncertainty Shape Energy Efficiency in the United States? Evidence From Wavelet Quantile Regression

Business Strategy and the Environment, EarlyView.
ABSTRACT Improving energy efficiency is a central pillar of climate mitigation strategies, energy security, and sustainable economic growth, particularly in energy‐intensive economies such as the United States. This study investigates the nonlinear and distribution‐dependent effects of energy prices, financial conditions, economic policy uncertainty ...
Busra Agan Celik
wiley   +1 more source

Cloud–Edge–End Collaborative Federated Learning: Enhancing Model Accuracy and Privacy in Non-IID Environments

Sensors
Cloud–edge–end computing architecture is crucial for large-scale edge data processing and analysis. However, the diversity of terminal nodes and task complexity in this architecture often result in non-independent and identically distributed (non-IID ...
Ling Li, Lidong Zhu, Weibang Li
doaj   +1 more source

Unlocking Federated Learning for ESG Reporting: Prioritizing Critical Adoption Challenges in an Emerging Economy Context

Business Strategy and the Environment, EarlyView.
ABSTRACT The growing focus on environmental, social, and governance (ESG) issues has prompted organizations to explore innovative ways to manage their businesses. It has become imperative for organizations to adopt ESG reporting. The applications of federated learning help to enhance the scalability and credibility of ESG reporting in contemporary ...
Naveen Virmani, Srikant Gupta, Koppiahraj Karuppiah, Jose Arturo Garza‐Reyes   +3 more
wiley   +1 more source

Interventional Mitral Valve Edge‐to‐Edge Repair in Patients Above 85 Years of Age

Catheterization and Cardiovascular Interventions, EarlyView.
ABSTRACT Background Mitral valve transcatheter‐edge‐to‐edge repair (M‐TEER) is routinely performed in patients with severe mitral regurgitation (MR) at high operative risk, frequently including elderly patients. Patients ≥ 85 years, however, are frequently excluded in clinical studies.
Florian Jürgens, Florian Schindhelm, Mohammed Abusharekh, Jürgen Kampf, Matthias Totzeck, Fadi Al‐Rashid, Peter Lüdike, Tienush Rassaf, Amir A. Mahabadi   +8 more
wiley   +1 more source

Non-IID scenario: 10-fold cross validation results with varying C.

, 2020
Non-IID scenario: 10-fold cross validation results with varying C.
Zeng Fu (8727135), Dianbo Liu (8311149), Li Huang (107408), Yifeng Yin (2992161), Hao Deng (409186), Shifa Zhang (8727138)   +5 more
core   +1 more source

Handling Non-IID Data in Federated Learning : An Experimental Evaluation Towards Unified Metrics

, 2023
Recent research has demonstrated that Non-Identically Distributed (Non-IID) data can negatively impact the performance of global models constructed in federated learning. To address this concern, multiple approaches have been developed.
Haller, Marc,, Lenz, Christian, Lenz, Christian,, Nachtigall, Robin,, Awayshehl, Feras M.,, Awayshehl, Feras M., Alawadi, Sadi,, Haller, Marc, Alawadi, Sadi, Nachtigall, Robin   +9 more
core   +1 more source