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cs.LG2025
Few-Shot Learning for Industrial Time Series: A Comparative Analysis Using the Example of Screw-Fastening Process Monitoring
Xinyuan Tu
Few-shot learning (FSL) has shown promise in vision but remains largely unexplored for \emph{industrial} time-series data, where annotating every new defect is prohibitively expens…
cs.LG2024
Meta-TTT: A Meta-learning Minimax Framework For Test-Time Training
Chen Tao, Li Shen, Soumik Mondal
Test-time domain adaptation is a challenging task that aims to adapt a pre-trained model to limited, unlabeled target data during inference. Current methods that rely on self-super…