Results 41 to 50 of about 4,684 (203)

Dap-FL: Federated Learning Flourishes by Adaptive Tuning and Secure Aggregation

IEEE Transactions on Parallel and Distributed Systems, 2023
Federated learning (FL), an attractive and promising distributed machine learning paradigm, has sparked extensive interest in exploiting tremendous data stored on ubiquitous mobile devices. However, conventional FL suffers severely from resource heterogeneity, as clients with weak computational and communication capability may be unable to complete ...
Qian Chen 0032, Zilong Wang 0001, Jiawei Chen 0010, Haonan Yan, Xiaodong Lin 0001   +4 more
openaire   +2 more sources

What Drives CSR Performance: Structures, Declarations or Values?

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Sustainability and corporate social responsibility (CSR) are increasingly central to strategic management, yet a gap persists between formal commitments and actual practice. The study explores the structural and value‐based predictors of the institutional integration of CSR and sustainability, with a focus on the mediating role of the CSR ...
Pavla Vrabcová, Lukáš Falát, Hana Urbancová, Peter Madzík   +3 more
wiley   +1 more source

LiD-FL: Towards List-Decodable Federated Learning

Proceedings of the AAAI Conference on Artificial Intelligence
Federated learning is often used in environments with many unverified participants. Therefore, federated learning under adversarial attacks receives significant attention. This paper proposes an algorithmic framework for list-decodable federated learning, where a central server maintains a list of models, with at least one guaranteed to perform well ...
Hong Liu, Liren Shan, Han Bao, Ronghui You, Yuhao Yi, Jiancheng Lv   +5 more
openaire   +2 more sources

Microbiome and aging: Trajectories of microbiome age across human ecosystems and their systemic effects

iMeta, EarlyView.
Microbiome age (MA) has emerged as an innovative biomarker of biological aging, reflecting host aging trajectories through dynamic alterations in microbial composition, function, and host–microbe interactions across multiple body ecosystems. Diverse computational strategies—including traditional machine learning, deep learning, and multi‐omics ...
Zhexin Ni, Jiaojiao Xie, Zhichun Zhang, Keming Zhang, Jie Ding, Mingyang Chang, Ying Su, Yunan Zhang, Mingfei Yao, Chengyuan Wang, Yan Yan, Wenjie Fang, Hainv Gao, Xuecong Tian, Yangshuo Li, Xinlin Zhu, Wen Zhang, Wanqing Liao, Gaoyuan Xu, Guojing Chen, Xiaoyi Lv, Chaoqin Yu, Weihua Pan, Vadim Molodtsov, Lanjuan Li, Yue Gao, Wei Zhou   +26 more
wiley   +1 more source

A Study of Federated Deep Learning for Building Indoor Climate Forecasting

IEEE Access
This study investigates federated deep learning for multi-horizon indoor climate forecasting in historic buildings. Unlike traditional centralized or isolated local learning approaches, this work explores federated learning (FL) as a solution that ...
Zhongjun Ni, Magnus Karlsson, Shaofang Gong   +2 more
doaj   +1 more source

Decentralized Machine Learning Training: A Survey on Synchronization, Consolidation, and Topologies

IEEE Access, 2023
Federated Learning (FL) has emerged as a promising methodology for collaboratively training machine learning models on decentralized devices. Notwithstanding, the effective synchronization and consolidation of model updates originating from diverse ...
Qazi Waqas Khan, Anam Nawaz Khan, Atif Rizwan, Rashid Ahmad, Salabat Khan, Do-Hyeun Kim   +5 more
doaj   +1 more source

Curriculum Guidelines for Social and Behavioral Sciences in Predoctoral Dental Education

Journal of Dental Education, EarlyView.
ABSTRACT Social and behavioral sciences are an integral part of predoctoral dental education, given the important role of social and behavioral factors in oral health, dentist‐patient communication, the provision of person‐centered care, and patients’ experience of dental treatment and their treatment outcomes.
Cameron L. Randall, Casey D. Wright, Dolores Cannella, Jessica G. Hinz, Daniel W. McNeil, Drashty P. Mody, Gary Pape, Yun Saksena, Vaishali Singhal, Lance Brendan Young, Stuart M. Schrader   +10 more
wiley   +1 more source

Federated Learning (FL) Model of Wind Power Prediction

IEEE Access
Wind power is a cheap renewable energy that plays an important role in the economic development of a country. Identifying potential locations for energy production is challenging due to the diverse relationship between wind power potential and the weather characteristics of a location.
Amal Alshardan, Sidra Tariq, Rab Nawaz Bashir, Oumaima Saidani, Rashid Jahangir   +4 more
openaire   +2 more sources

Artificial Intelligence in Dermatology: Current Applications and Future Directions

JEADV Clinical Practice, EarlyView.
This scoping review of 56 studies maps AI applications in dermatology. Image‐based classification for skin cancer detection dominates (48%), followed by clinical decision support (21%), teledermatology triage (11%), and predictive analytics (11%). While deep learning algorithms demonstrate diagnostic performance comparable to clinicians in controlled ...
Sofía Pérez‐Lalinde, Francisco Flores   +1 more
wiley   +1 more source

FedCLCC: A personalized federated learning algorithm for edge cloud collaboration based on contrastive learning and conditional computing

Defence Technology
Federated learning (FL) is a distributed machine learning paradigm for edge cloud computing. FL can facilitate data-driven decision-making in tactical scenarios, effectively addressing both data volume and infrastructure challenges in edge environments ...
Kangning Yin, Xinhui Ji, Yan Wang, Zhiguo Wang   +3 more
doaj   +1 more source