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Found 3 papers, 0 papers with code
Sequential Maximum Margin Classifiers for Partially Labeled Data
In many real-world applications, data is not collected as one batch, but sequentially over time, and often it is not possible or desirable to wait until the data is completely gathered before analyzing it.
Latent Laplacian Maximum Entropy Discrimination for Detection of High-Utility Anomalies
Data-driven anomaly detection methods suffer from the drawback of detecting all instances that are statistically rare, irrespective of whether the detected instances have real-world significance or not.
Unsupervised Anomaly Detection
Vocal Bursts Intensity Prediction
Efficient Distributed Estimation of Inverse Covariance Matrices
In distributed systems, communication is a major concern due to issues such as its vulnerability or efficiency.
