Results 71 to 80 of about 91,570 (234)

Distributed consensus problem with caching on federated learning framework

International Journal of Distributed Sensor Networks, 2022
Federated learning framework facilitates more applications of deep learning algorithms on the existing network architectures, where the model parameters are aggregated in a centralized manner.
Xin Yan, Yiming Qin, Xiaodong Hu, Xiaoling Xiao   +3 more
doaj   +1 more source

Federated Learning from Small Datasets

, 2021
Federated learning allows multiple parties to collaboratively train a joint model without sharing local data. This enables applications of machine learning in settings of inherently distributed, undisclosable data such as in the medical domain. In practice, joint training is usually achieved by aggregating local models, for which local training ...
Kamp, Michael, Fischer, Jonas, Vreeken, Jilles   +2 more
openaire   +5 more sources

Citizen Engagement for Social and Technological Innovation in Sustainable Energy Systems

Advanced Energy and Sustainability Research, EarlyView.
This study underscores the potential of citizen participation in the energy transition by providing insights to foster citizen‐driven innovation. An analysis of energy communities, one of the most dynamic innovations in the energy sector, reveals that these models can be citizen‐led initiatives regarding their operational and organizational structure ...
Ana Belén Cristóbal, Cristina Sanz‐Cuadrado, Kiane Alves e Silva, Luis Narvarte   +3 more
wiley   +1 more source

Disentangling the relationships between denomination of origin regulatory councils activities and Spanish wineries' export performance

Agribusiness, EarlyView.
Abstract World markets for quality differentiated agri‐food products are highly competitive, presenting significant challenges for firms aiming to compete effectively. Government agencies and business organizations often implement various export promotion policies to address these challenges.
Nicolás Depetris‐Chauvin, Marta Fernández‐Olmos   +1 more
wiley   +1 more source

An Watermarking Framework of Active Protection Model for Secure Federated Learning [PDF]

Jisuanji gongcheng
As a new paradigm in deep learning, federated learning allows multiple parties to jointly train deep learning models while ensuring that data remains on the clients' local devices.
CHEN Xianyi, DING Sizhe, WANG Kang, YAN Leiming, FU Zhangjie
doaj   +1 more source

The Role of Certifications in Improving Household Food Security Among Peruvian Farmers

Agribusiness, EarlyView.
ABSTRACT Achieving global food security requires sustainable transformations in agri‐food systems. Voluntary Sustainability Standards (VSS) such as Organic and Fairtrade aim to internalize certain social and environmental costs while promoting more equitable value distribution, improved market access, and sustainable production practices.
Lisa‐Marie Schulte, Awudu Abdulai
wiley   +1 more source

Association Between Liver Function Grade and Post‐Hepatectomy Liver Failure in Patients With Hepatocellular Carcinoma: A Latent Class Analysis

Annals of Gastroenterological Surgery, EarlyView.
We retrospectively analyzed clinical data from patients who underwent hepatectomy for hepatocellular carcinoma (HCC) using LCA‐based grading system. These findings provide a new risk stratification framework for the design of precision surgery to treat patients with HCC.
Ling Liu, Jintao Zheng, Ye Wang, Chenao Yang, Jiachen Zhang, Changku Jia   +5 more
wiley   +1 more source

Federated Learning-Based Framework: A New Paradigm Proposed for Supply Chain Risk Management

Engineering Proceedings
This paper proposes federated learning-based frameworks for supply chain risk management to address data-sharing constraints. To validate, centralized federated learning with horizontal data was applied for delivery delay prediction using datasets from ...
Thanh Tuan Nguyen, Abdelghani Bekrar, Thi Muoi Le, Abdelhakim Artiba, Tarik Chargui, Thi Thu Huong Trinh, Ahmed Snoun   +6 more
doaj   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Chained Anomaly Detection Models for Federated Learning: An Intrusion Detection Case Study

Applied Sciences, 2018
The adoption of machine learning and deep learning is on the rise in the cybersecurity domain where these AI methods help strengthen traditional system monitoring and threat detection solutions.
Davy Preuveneers, Vera Rimmer, Ilias Tsingenopoulos, Jan Spooren, Wouter Joosen, Elisabeth Ilie-Zudor   +5 more
doaj   +1 more source