NeurIPS-2017
means being highly related to my personal research interest.
Noise
- Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization
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Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks
- We propose a conditional random field (CRF) [2] model to represent the relationship between noisy and clean labels, and we show how modern deep CNNs can gain robustness against label noise using our proposed structure. We model the clean labels as latent variables during training, and we design our structure such that the latent variables can be inferred efficiently.
