Privacy-preserving gradient boosting tree: Vertical federated learning for collaborative bearing fault diagnosis

Keyphrases

• Privacy-preserving 100%
• Gradient Boosted Trees 100%
• Bearing Fault Diagnosis 100%
• Vertical Federated Learning 100%
• Collaborative Bearing 100%
• Data Privacy 66%
• Model Performance 33%
• Learning Model 33%
• Diagnosis Approach 33%
• Fault Diagnosis 33%
• Negative Effects 33%
• Anonymity 33%
• Homomorphic Encryption 33%
• Low Quality Data 33%
• Model Privacy 33%
• Model Information 33%
• Data-driven Fault Diagnosis 33%
• Bearing Fault 33%
• Collaborative Fault Diagnosis 33%
• Fault Diagnosis Model 33%
• Fault Case 33%
• Data Silos 33%
• Challenging Issues 33%
• Typical Scenario 33%
• Boosted Trees 33%
• Autoencoder Model 33%
• Encryption Protocols 33%

Computer Science

• Federated Learning 100%
• Privacy Preserving 100%
• Fault Diagnosis 100%
• Gradient Boosting Tree 100%
• Data Privacy 40%
• Information Model 20%
• Homomorphic Encryption 20%
• Performance Model 20%
• Autoencoder 20%
• Case Study 20%
• Anonymity 20%
• Negative Effect 20%