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We consider classification in the presence of class-dependent asymmetric label noise with unknown noise probabilities.
Smooth discrimination analysis
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Classification with asymmetric label noise: Consistency and maximal denoising
Scott, C., Blanchard, G., and Handy, G · 2013
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Dasgupta, S. and Kpotufe, S · 2014
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Biau, G. and Devroye, L · 2015
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Inouye, D. I., Ravikumar, P., Das, P., and Dutta, A · 2017
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Jiang, H. and Kpotufe, S · 2017
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Gao, W., Niu, X., and Zhou, Z · 2018
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Menon, A. K., van Rooyen, B., and Natarajan, N · 2018
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Scott, C · 2015
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Classification with asymmetric label noise: Consistency and maximal denoising
Blanchard, G., Flaska, M., Handy, G., Pozzi, S., and Scott, C · 2016
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Cost-sensitive learning with noisy labels
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Non-asymptotic uniform rates of consistency for k-nn regression
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