Severe data starvation, architectural heterogeneity and Byzantine vulnerabilities fundamentally impede the deployment of robust multiclass classification models in decentralised edge environments. To address these intertwined challenges, we propose
fusion isomerism learning (FusionIL)
, a secure and domain‐agnost...
Zhi-Hao Hao, Long-Bing Cao, Han Yu et al.· CAAI Transactions on Intelli...· 0 citations
Code, per-run results, tables and figures for the manuscript "Communication-efficient split federated learning for patient-independent ECG classification". The ECG databases are not included.
Venkatesh Janarthanan, Viswanathan A· Zenodo (CERN European Organi...· 0 citations
A median filter removes impulsive noise by sorting a few neighbouring samples and picking the middle one. Filters of this family (rank-order or order-statistic filters) need no multiplications, cannot be thrown off by a few wild samples, and their output never moves more than their input does. They were popular in the...
Juan Carlos del Rio Romero· Zenodo (CERN European Organi...· 0 citations
Résumé (FR) Ce document, produit avec l'assistance de Gemini 3 Raisonnement, est publié sous licence Apache 2.0. Il constitue une publication défensive volontaire (antériorité) entrant dans l'état de la technique selon les législations applicables (EPC Art. 54(2); French IPC Art. L 611-11; cf. 35 U.S.C. §102(a)). Face...
Xavier Pillet· Zenodo (CERN European Organi...· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
A Systematic Review Protocol “Beyond Diagnostic Accuracy: Calibration and Predictive Uncertainty of Artificial Intelligence Models for Oral and Dental Disease Diagnosis” Title of the ReviewBeyond Diagnostic Accuracy: Calibration and Predictive Uncertainty of Artificial Intelligence Models for Oral and Dental Disease Di...
A median filter removes impulsive noise by sorting a few neighbouring samples and picking the middle one. Filters of this family (rank-order or order-statistic filters) need no multiplications, cannot be thrown off by a few wild samples, and their output never moves more than their input does. They were popular in the...
Juan Carlos del Rio Romero· Zenodo (CERN European Organi...· 0 citations
Code, per-run results, tables and figures for the manuscript "Communication-efficient split federated learning for patient-independent ECG classification". The ECG databases are not included.
Venkatesh Janarthanan, Viswanathan A· Zenodo (CERN European Organi...· 0 citations
A median filter removes impulsive noise by sorting a few neighbouring samples and picking the middle one. Filters of this family (rank-order or order-statistic filters) need no multiplications, cannot be thrown off by a few wild samples, and their output never moves more than their input does. They were popular in the...
Juan Carlos del Rio Romero· Zenodo (CERN European Organi...· 0 citations
Re-created code for the PLoS One article e0322749 (2025): nuclei segmentation (SegNet) and classification (DenseNet121) on PanNuke with Hyperband tuning, TensorFlow Lite quantization and federated learning. Includes the result tables underlying the reproduced results.
Anjir Ahmed Chowdhury, S M Hasan Mahmud, Md Palash Uddin et al.· Zenodo (CERN European Organi...· 0 citations
A median filter removes impulsive noise by sorting a few neighbouring samples and picking the middle one. Filters of this family (rank-order or order-statistic filters) need no multiplications, cannot be thrown off by a few wild samples, and their output never moves more than their input does. They were popular in the...
Juan Carlos del Rio Romero· Zenodo (CERN European Organi...· 0 citations
The proliferation of multi-cloud architectures has intensified challenges in phishing detection, as security intelligence becomes fragmented across heterogeneous cloud infrastructures governed by stringent privacy regulations and data sovereignty constraints. Conventional centralized threat detection paradigms necessit...
Shakir Khan, Arvind Panwar, Achin Jain et al.· Scientific Reports· 0 citations
Re-created code for the PLoS One article e0322749 (2025): nuclei segmentation (SegNet) and classification (DenseNet121) on PanNuke with Hyperband tuning, TensorFlow Lite quantization and federated learning. Includes the result tables underlying the reproduced results.
Anjir Ahmed Chowdhury, S M Hasan Mahmud, Md Palash Uddin et al.· Zenodo (CERN European Organi...· 0 citations
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
