Results 31 to 40 of about 1,993,316 (300)

Effective, Explainable, and Trustworthy Client Selection in Federated Learning

open access: yesIEEE Open Journal of the Computer Society
Client selection is a pivotal process in Federated Learning (FL). Despite their contributions to the learning effectiveness of global and local models, most current client selection approaches overlook the importance of ensuring trustworthiness and ...
Edwin F. Castillo   +2 more
doaj   +1 more source

Experimental Evaluation and Analysis of Federated Learning in Edge Computing Environments

open access: yesIEEE Access, 2023
Federated learning (FL) is a machine learning system that allows a network of devices to train a model without centralized data. This characteristic makes FL an ideal choice for machine learning using user data while maintaining privacy.
Pham Khanh Quan   +2 more
doaj   +1 more source

Fairness-Aware Client Selection for Federated Learning

open access: yes2023 IEEE International Conference on Multimedia and Expo (ICME), 2023
Accepted by ICME ...
Yuxin Shi   +3 more
openaire   +2 more sources

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

open access: yesMolecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur   +11 more
wiley   +1 more source

Circulating microRNA signatures of cachexia and cancer in Canis familiaris as a comparative oncology model for human disease

open access: yesMolecular Oncology, EarlyView.
Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park   +6 more
wiley   +1 more source

CAREAssist client satisfaction survey [PDF]

open access: yes, 2006
This archived document is maintained by the Oregon State Library as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Title from PDF title page (viewed on Sept.

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Adaptive Federated Learning With Reinforcement Learning-Based Client Selection for Heterogeneous Environments

open access: yesIEEE Access
This study introduces an Adaptive Federated Learning (AFL) framework designed to address the challenges of data heterogeneity, resource imbalance, and communication constraints in decentralized learning environments.
Shamim Ahmed   +3 more
doaj   +1 more source

Efficient Client Selection in Federated Learning

open access: yes2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC)
Federated Learning (FL) enables decentralized machine learning while preserving data privacy. This paper proposes a novel client selection framework that integrates differential privacy and fault tolerance. The adaptive client selection adjusts the number of clients based on performance and system constraints, with noise added to protect privacy ...
William Marfo   +2 more
openaire   +2 more sources

Five‐Year Disease Progression in Synuclein Seeding Positive Sporadic Parkinson's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To provide a comprehensive description of disease progression in synuclein seeding assay (SAA) positive sporadic Parkinson Disease participants, using Neuronal Synuclein Disease integrated biological and functional impairment staging framework.
Paulina Gonzalez‐Latapi   +19 more
wiley   +1 more source

Other title: Title from HTML header (viewed Nov. 9, 2011): Judicial Selection Commission [PDF]

open access: yes, 2011
Updated irregularly; Began in 2002?; Title from main search screen (publisher's Web site, viewed Nov. 9, 2011).; At head of title: State of Connecticut.; Harvested from the web on 11/10/11Official website of the Connecticut Judicial Selection Commission.

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