Datasets often incorporate various functional patterns related to different aspects or regimes, which are typically not equally present throughout the dataset. We propose a novel partitioning ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

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A non-standard, fractal-inspired sorting algorithm with adaptive multi-pivot partitioning and k-way heap merging. Achieves near O(n log log n) performance in ideal cases.

Already a presence in West Texas, Cipher Mining is in the midst of adding to that presence. The New York City-based company is nearing completion of its Black Pearl Data Center, located at 11786 ...

Abstract: Frequent Itemset Mining (FIM) is one of the classical and well-adopted descriptive approaches in data mining. However classical algorithms of FIM like Apriori method suffer from higher I/O ...

Abstract: Existing outlier mining algorithms such as FOMAUC are based on density-grid. These algorithms have the problems of inefficiency and bad-adaptability for various data sets, so this paper ...