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03/27/2023
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error
Estimating the generalization performance is practically challenging on ...
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12/08/2022
Logit Clipping for Robust Learning against Label Noise
In the presence of noisy labels, designing robust loss functions is crit...
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06/17/2022
Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets
Deep neural networks usually perform poorly when the training dataset su...
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05/30/2022
ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection
Class-incremental learning (CIL) learns a classification model with trai...
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05/19/2022
Mitigating Neural Network Overconfidence with Logit Normalization
Detecting out-of-distribution inputs is critical for safe deployment of ...
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01/16/2022
GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation
This paper studies weakly supervised domain adaptation(WSDA) problem, wh...
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06/21/2021
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise
Learning with noisy labels is a practically challenging problem in weakl...
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10/08/2019