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An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series
In order to realize the adaptive selection of detectors and run-time parameters according to the input time series, the outputs of FCN are the inputs of two sub-networks: the detector selection network and the run-time parameters selection network.
AMAD: Adversarial Multiscale Anomaly Detection on High-Dimensional and Time-Evolving Categorical Data
Anomaly detection is facing with emerging challenges in many important industry domains, such as cyber security and online recommendation and advertising.
Visualizing and Understanding Deep Neural Networks in CTR Prediction
Recently, many works have been done on visualizing and analyzing the mechanism of deep neural networks in the areas of image processing and natural language processing.
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