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Chapter and Conference Paper
Estimating Cartesian Compression via Deep Learning
We introduce a learning architecture that can serve compression while it also satisfies the constraints of factored reinforcement learning. Our novel Cartesian factors enable one to decrease the number of variabl...
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Chapter and Conference Paper
Robust Detection of Anomalies via Sparse Methods
The problem of anomaly detection is a critical topic across application domains and is the subject of extensive research. Applications include finding frauds and intrusions, warning on robot safety, and many othe...