The proposed DP framework integrates automated mitigation unified risk fusion, guideline-based control verification, and recommendation reporting to offer proactive fraud prevention and comprehensive risk assessment and achieves superior accuracy, precision, recall, and F1-score.
Artificial intelligence has the potential to transform clinical decision-making for patients presenting with infertility by enabling objective, high-throughput, and personalised assessment of semen samples, but these tools should be used to augment rather than replace clinical expertise until models have been prospecti...
ElasticScale is presented, an elastic orchestration system that organizes heterogeneous accelerators into disaggregated rollout and trainer instances, via a HeterogeneousRayWorkerGroup abstraction that manages non-uniform hardware topologies and a multi-instance Federated Weight Averaging protocol that aggregates updat...
Wei-An Lin, M. Reza, Talha Nayyar et al.· Proceedings of the 21st Work...· 0 citations
The prototype demonstrates a practical institution-local distributed file system (DFS) for content-addressed acquisition staging that supports verifiable digital collection objects and a federated storage model for collaborating GLAM institutions.
Joachim Snellings, Jasper Funk-Smit, Margot Belot et al.· 0 citations
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This work proposes the graph-based learning individual intrinsic reward heterogeneous-agent proximal policy optimization (GLIIR-HAPPO) algorithm, a novel heterogeneous multi-agent reinforcement learning (MARL) framework that fundamentally overcomes this impasse by systematically decomposing the original coupled optimiz...
Bo-Kai Xu, Jia-Yi Zhang, Shuai-Fei Chen et al.· 0 citations
A federated Bayesian protocol for learning population-scale adverse-event surveillance as a distinct belief layer of the surgical digital twin is proposed, and a federated Bayesian protocol for learning it under formal privacy guarantees is evaluated.
This work quantifies privacy posture with k-anonymity, l-diversity and t-closeness, aggregate them into a composite Privacy-Posture Index (PPI), and measures residual re-identification across eight transformation configurations on internal PCAP captures and the public Idaho Labs 5GAD corpus.
Nikolaos Kekatos, Apostolos Valiakos, Alexios Lekidis et al.· 0 citations
TwinFedSeg, a federated learning framework guided by an anatomical twin state for multimodal medical image segmentation, is proposed, which consistently outperforms representative federated methods.
Hao-Ran Zhou, Ying-Zhi Qin, Peng-Fei Mu et al.· IEEE journal of biomedical a...· 0 citations
MediNet is a comprehensive server-client Federated learning (FL) platform that allows hospitals and research centers to train Machine Learning (ML) and DL models without moving or exposing sensitive data.
Ramon Mateo-Navarro, David Sarrat-González, Dolors Pelegrí-Sisó et al.· Bioinformatics· 0 citations
Skin cancer is a major global health concern, and early detection and accurate lesion delineation are important for effective diagnosis and treatment planning. Automated skin lesion analysis can assist dermatologists, with lesion segmentation serving as a fundamental step in computer-aided diagnostic systems. Conventio...
A. Pal, Ganesh Patidar, Bikash Santra· 0 citations
Conventional decentralized federated learning (DFL) often focuses on clients, with each client maintaining a model copy, performing updates individually, and undertaking model exchange and integration. While fully leveraging computational resources can shorten training times, it can also lead to significant computation...
Kota Maejima, Takayuki Nishio, Asato Yamazaki et al.· 0 citations
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
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