PCA-Triage adaptively sets sensor sampling rates from incremental PCA loadings to meet bandwidth limits while preserving downstream inference F1 scores close to full-data performance.
Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
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Parametric OpInf learns and interpolates reduced-order models from CFD data for PECVD purging flow, reporting 9.32% max error on unseen parameters and 142x speedup.
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PCA-Driven Adaptive Sensor Triage for Edge AI Inference
PCA-Triage adaptively sets sensor sampling rates from incremental PCA loadings to meet bandwidth limits while preserving downstream inference F1 scores close to full-data performance.
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Parametric Operator Inference to Simulate the Purging Process in Semiconductor Manufacturing
Parametric OpInf learns and interpolates reduced-order models from CFD data for PECVD purging flow, reporting 9.32% max error on unseen parameters and 142x speedup.