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Computationally and Memory-Efficient Robust Predictive Analytics Using Big Data
April 1, 2024, 4:41 a.m. | Daniel Menges, Adil Rasheed
cs.LG updates on arXiv.org arxiv.org
Abstract: In the current data-intensive era, big data has become a significant asset for Artificial Intelligence (AI), serving as a foundation for developing data-driven models and providing insight into various unknown fields. This study navigates through the challenges of data uncertainties, storage limitations, and predictive data-driven modeling using big data. We utilize Robust Principal Component Analysis (RPCA) for effective noise reduction and outlier elimination, and Optimal Sensor Placement (OSP) for efficient data compression and storage. The …
abstract analytics artificial artificial intelligence arxiv become big big data challenges cs.ai cs.lg current data data-driven eess.iv fields foundation insight intelligence limitations memory modeling predictive predictive analytics robust storage study through type
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