Results 91 to 100 of about 1,704,441 (287)

Weighted Ensemble Distillation in Federated Learning with Non-IID Data

open access: yes, 2022
Federated distillation (FD) is a novel algorithmic idea for federated learning (FL) that allows clients to use heterogeneous model architectures. This is achieved by distilling aggregated local model predictions on an unlabeled auxiliary dataset into ...
Eriksson, Oscar
core  

When Biology Meets Medicine: A Perspective on Foundation Models

open access: yesAdvanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu   +3 more
wiley   +1 more source

Assessing Progression Independent of Relapse Activity in Multiple Sclerosis Using a Patient‐Reported Disability Measure and Self‐Administered Neuroperformance Outcomes

open access: yesAnnals of Neurology, EarlyView.
Objective The objective of this study was to investigate the ability of patient‐reported/administered outcomes to capture disability worsening and progression independent of relapse activity (PIRA) in multiple sclerosis (MS). Methods We included patients from the longitudinal multicenter MS PATHS cohort with ≥3 assessments and >6 months follow‐up. PIRA
Evy M. Reinders   +40 more
wiley   +1 more source

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

open access: yesSensors
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

Federated Loss Exploration for Improved Convergence on Non-IID Data

open access: yes
Internò C, Olhofer M, Jin Y, Hammer B. Federated Loss Exploration for Improved Convergence on Non-IID Data. In: 2024 International Joint Conference on Neural Networks (IJCNN). IEEE International Joint Conference on Neural Networks (IJCNN).
Hammer, Barbara ; https://orcid.org/   +3 more
core   +1 more source

Dental anomalies in Pleistocene African hippopotamuses from Olduvai Bed II

open access: yesThe Anatomical Record, EarlyView.
Abstract Hippopotamuses are key palaeoenvironmental indicators in African Pleistocene ecosystems due to their ecological dependence on permanent water bodies and their frequent representation in the fossil record. This study examines dental anomalies in Hippopotamus cf. gorgops from several localities in Bed II of Olduvai Gorge (Tanzania), dated to ca.
Darío Fidalgo   +4 more
wiley   +1 more source

Genomic Structural Variations Provide Insights Into Litter Size and Teat Number Traits in Hu Sheep

open access: yesAnimal Research and One Health, EarlyView.
Here, we conducted whole genome sequencing on 300 Hu sheep with an average depth of 16.51X. Two candidate genes associated with litter size and teat number traits were identified, namely MAST2 and AFDN. ABSTRACT Litter size and the teat number are important economic indicators in sheep production.
Xin Xiang   +3 more
wiley   +1 more source

Homologous membrane wrapped ZIF‐8 nanoparticles accelerate differentiation of neural stem cell for spinal cord injury therapy

open access: yesBMEMat, EarlyView.
Homologous membrane wrapped ZIF‐8 nanoparticles were proposed to improve biocompatibility and targeting ability to neural stem cells (NSCs). ZIF‐8‐SCM NPs exhibit pH responsiveness, thereby generating an intracellular Zn2+ storm to accelerate neural differentiation through calcium and MAPK signaling pathways. Moreover, they promote function recovery in
Jie Wang   +11 more
wiley   +1 more source

What Constitutes an Attractive Product‐as‐a‐Service Offer? Examining Consumer Preferences for (Circular) Business Patterns

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT Little is known about consumer preferences for combinations of circular business model patterns, despite their potential to benefit the design of product services. This study examines consumer preferences for product‐as‐a‐service offers, combined with circular product attributes, across Sweden and the Netherlands.
Steven Sarasini   +5 more
wiley   +1 more source

CHPFL: Clustered adaptive hierarchical federated learning for edge-level personalization

open access: yesHigh-Confidence Computing
Federated learning faces challenges with non-IID data distributions, often resulting in suboptimal performance for individual clients with the global model. To address this issue, we propose a clustered hierarchical personalized federated learning (CHPFL)
Lihua Song   +4 more
doaj   +1 more source

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