Natural Selection (NS) dynamically reweights DNN training losses by estimating each sample's competitive status inside groups assembled as composite images.
mixup: Beyond empirical risk minimization,
2 Pith papers cite this work. Polarity classification is still indexing.
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A two-stage iterative method with OR-Gate top-k selection filters noisy labels during training of speaker verification models on VoxCeleb datasets.
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Evolution-Inspired Sample Competition for Deep Neural Network Optimization
Natural Selection (NS) dynamically reweights DNN training losses by estimating each sample's competitive status inside groups assembled as composite images.
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Robust Training for Speaker Verification against Noisy Labels
A two-stage iterative method with OR-Gate top-k selection filters noisy labels during training of speaker verification models on VoxCeleb datasets.