TL-LLP is a transfer-learning extension of SVR-based label-proportions classification that models each input as lying in a bounded noise region and is claimed to be more accurate and noise-robust, though the uncertainty update actually fits the noise.
Estimating labels from label proportions
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Transfer Learning-Based Label Proportions Method with Data of Uncertainty
TL-LLP is a transfer-learning extension of SVR-based label-proportions classification that models each input as lying in a bounded noise region and is claimed to be more accurate and noise-robust, though the uncertainty update actually fits the noise.