Semantic Scholar
metadata only
Class-Imbalance Privacy-Preserving Federated Learning for Decentralized Fault Diagnosis With Biometric Authentication
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Machine Learning-Powered Anomaly Detection: Enhancing Data Security and Integrity#328753
- Hierarchical proof of trust a Byzantine fault tolerant federated learning framework for industrial IoT applications.#371734
- On the (In)security of Peer-to-Peer Decentralized Machine Learning#134002
- Privacy-Preserving Data Drift Detection and Recovery for Large-Scale LLM Applications via Proxy Representations#441718
- Augmenting distance protection with a data-based approach to fault classification under uncertainty / Sarah Anhaus, Arlind Damjani, Willem Paul Leterme#629034
Record · ID 303027
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive