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06/17/2023
Linearly-scalable learning of smooth low-dimensional patterns with permutation-aided entropic dimension reduction
In many data science applications, the objective is to extract appropria...
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12/22/2021
Robust learning of data anomalies with analytically-solvable entropic outlier sparsification
Entropic Outlier Sparsification (EOS) is proposed as a robust computatio...
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03/30/2021
On Computationally-Scalable Spatio-Temporal Regression Clustering of Precipitation Threshold Excesses
Focusing on regression based analysis of extremes in a presence of syste...
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02/08/2020