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ActionBert: Leveraging User Actions for Semantic Understanding of User Interfaces
Our methodology is designed to leverage visual, linguistic and domain-specific features in user interaction traces to pre-train generic feature representations of UIs and their components.
Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning
Specifically, we first train a temporal deep learning model, using only normal HPC readings from legitimate processes that run daily in these power-grid systems, to model the normal behavior of the power-grid controller.
Time Series Segmentation through Automatic Feature Learning
As such, we have seen many recent IoT data sets include annotations with a human expert specifying states, recorded as a set of boundaries and associated labels in a data sequence.
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