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10/23/2022
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation
Rotation is frequently listed as a candidate for data augmentation in co...
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06/03/2021
Generalized Domain Adaptation
Many variants of unsupervised domain adaptation (UDA) problems have been...
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03/08/2021
A Novel Perspective for Positive-Unlabeled Learning via Noisy Labels
Positive-unlabeled learning refers to the process of training a binary c...
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11/03/2020
The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals
We propose a new optimization framework for aleatoric uncertainty estima...
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07/22/2020
Multi-Task Curriculum Framework for Open-Set Semi-Supervised Learning
Semi-supervised learning (SSL) has been proposed to leverage unlabeled d...
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03/30/2018
Parallel Grid Pooling for Data Augmentation
Convolutional neural network (CNN) architectures utilize downsampling la...
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03/30/2018
Joint Optimization Framework for Learning with Noisy Labels
Deep neural networks (DNNs) trained on large-scale datasets have exhibit...
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12/29/2017
Significance of Softmax-based Features in Comparison to Distance Metric Learning-based Features
The extraction of useful deep features is important for many computer vi...
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05/26/2017