CardioMix uses cardiac pattern-guided bidirectional fusion to mix labeled and unlabeled ECG data for better semi-supervised segmentation while keeping samples physiologically valid.
Fixmatch: Simplifying semi- supervised learning with consistency and confidence
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A semi-supervised temporal framework for cloud network intrusion detection that combines supervised learning with consistency regularization and selective pseudo-labeling to improve robustness against adversarial contamination and temporal drift.
citing papers explorer
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Bidirectional Fusion Guided by Cardiac Patterns for Semi-Supervised ECG Segmentation
CardioMix uses cardiac pattern-guided bidirectional fusion to mix labeled and unlabeled ECG data for better semi-supervised segmentation while keeping samples physiologically valid.
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Robust Semi-Supervised Temporal Intrusion Detection for Adversarial Cloud Networks
A semi-supervised temporal framework for cloud network intrusion detection that combines supervised learning with consistency regularization and selective pseudo-labeling to improve robustness against adversarial contamination and temporal drift.