s-step self-distillation is optimal among spectral shrinkage estimators for s-spiked covariance matrices and necessary for optimality.
Statistical and algorithmic insights for semi- supervised learning with self-training.arXiv preprint arXiv:2006.11006, 2020
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VBFDD-Agent transforms battery signals into descriptive texts and combines them with LLM reasoning and retrieval to provide interpretable fault diagnosis and maintenance suggestions for EV batteries.
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Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models
s-step self-distillation is optimal among spectral shrinkage estimators for s-spiked covariance matrices and necessary for optimality.
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VBFDD-Agent for Electric Vehicle Battery Fault Detection and Diagnosis: Descriptive Text Modeling of Battery Digital Signals
VBFDD-Agent transforms battery signals into descriptive texts and combines them with LLM reasoning and retrieval to provide interpretable fault diagnosis and maintenance suggestions for EV batteries.