Latest Research in Machine Learning

Top Research Topics in Machine Learning

• Machine Learning — 10 papers
• Anomaly Detection Techniques and Applications — 7 papers
• Software System Performance and Reliability — 4 papers
• Methodology — 2 papers
• Artificial Intelligence — 2 papers
• Thermal Analysis in Power Transmission — 2 papers
• Time Series Analysis and Forecasting — 1 papers
• GNSS positioning and interference — 1 papers
• Microplastics and Plastic Pollution — 1 papers
• Electrical Fault Detection and Protection — 1 papers

Highest-Cited Papers

1. Towards explainable anomaly detection for satellite telemetry
2. Time series one class classification: a systematic review of methods, applications, and challenges
3. A unified approach to robust classification in the presence of outliers
4. Scalable and Adaptive Log-based Anomaly Detection: A Synergistic Approach
5. GALLog: A Graph-based Log Anomaly Detection Method with Active Learning
6. Isolation-based Spherical Ensemble Representations for Tabular Anomaly Detection
7. GSLAD: Prototype-Regularized Graph Structure Learning for Multivariate Time Series Anomaly Detection
8. Optimal Transport for Efficient, Unsupervised Anomaly Detection on Industrial Data (2 citations)
9. Causal Wavelet Residual Learning with Observation-Support Gating for Industrial Sensor Anomaly Detection
10. Score-based Outlier Generation via Controlling the Radon-Nikodym Derivative
11. An intelligent optimization method for communication monitoring alarm threshold based on BeiDou satellite positioning data
12. Curvularia lunata drives biodeterioration of PVC secondary cable insulation involving surface colonization, moisture retention and chemical deterioration
13. Nonparametric framework for the definition, adaptive detection and probabilistic interpretation of outliers
14. Real-time and adaptive anomaly detection algorithm for cyclostationary models
15. Failure Mode, Effects, and Criticality Analysis (FMECA)-Based Fault Diagnosis of a High-Voltage Disconnect Switch
16. Scoring conventions reorder adaptation policies in streaming anomaly detection
17. Scoring conventions reorder adaptation policies in streaming anomaly detection
18. Differentiable Interval Bottlenecks for Interpretable Anomaly Detection in Numerical Data
19. A Metamorphic Testing Framework for Verification and Validation of Unsupervised Sensor Grouping in Smart Spaces via Spectral Clustering
20. Deja Vu in Plots: Leveraging Cross-Session Evidence with Retrieval-Augmented LLMs for Live Streaming Risk Assessment