Derives information-theoretic recovery thresholds for two intersecting lines with polynomial mass concentration near the intersection and matches them (up to polylog factors) via a spectral algorithm on a hypergraph built from nearly collinear triples.
IEEE Transactions on Information Theory 61(11), 6320–6342 (2015)
2 Pith papers cite this work. Polarity classification is still indexing.
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RoseCDL adds stochastic windowing and inline outlier detection to convolutional dictionary learning to enable scalable unsupervised anomaly detection via local reconstruction loss on large signals.
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Consistent line clustering using geometric hypergraphs
Derives information-theoretic recovery thresholds for two intersecting lines with polynomial mass concentration near the intersection and matches them (up to polylog factors) via a spectral algorithm on a hypergraph built from nearly collinear triples.
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RoseCDL: Robust and Scalable Convolutional Dictionary Learning for Rare event and Anomaly Detection
RoseCDL adds stochastic windowing and inline outlier detection to convolutional dictionary learning to enable scalable unsupervised anomaly detection via local reconstruction loss on large signals.