Field-level analysis examines how ranking algorithms shape consumer trust, visibility, and competition in local service ...
A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in ...
Abstract: The multi-reference alignment (MRA) problem involves reconstructing a signal from multiple noisy observations, each transformed by a random group element. In this paper, we focus on the ...
Recent advances in deep learning have enabled effective interpretation of neural activity patterns from electroencephalogram signals; however, challenges persist in invasive brain signals for ...
This project develops and evaluates multiple machine learning models to detect fraudulent transactions for FNB (First National Bank). The analysis encompasses comprehensive data exploration, feature ...
Abstract: Accurate decoding in electroencephalography (EEG) technology, particularly for rapid visual stimuli, remains challenging due to the low signal-to-noise ratio (SNR). Additionally, existing ...
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