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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...

    András Lőrincz, András Sárkány, Zoltán Á. Milacski in Artificial General Intelligence (2016)

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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...

    Zoltán Á. Milacski, Marvin Ludersdorfer, András Lőrincz in Neural Information Processing (2015)