Unsupervised or Indirectly Supervised Learning
Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning Seonghyun Ban
Previous approaches often downweight instances from irrelevant classes to mitigate the negative impact of class distribution mismatch on model training.
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A Novel Approach for Eff ective Multi-View Clustering with Information-Theoretic Perspective
Multi-view clustering (MVC) is a popular technique for improving clustering performance using various data sources.
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Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery
Recent advancements have shown promise in applying traditional Semi-Supervised Learning strategies to the task of Generalized Category Discovery (GCD).
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For instance, data augmentation consistency regularization [Sohn et al., 2020, Berthelot et al., 2019] generates pseudo-labels from the current model predictions on
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Dual Swap Disentangling
Zunlei Feng, Xinchao Wang, Chenglong Ke, An-Xiang Zeng, Dacheng Tao, Mingli Song
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Realistic Evaluationof Deep Semi-Supervised Learning Algorithms
Further, thetrainingprocedure (optimizer, numberoftrainingsteps, learningratedecayschedule, etc.) is notstandardized.
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The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning
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Unsupervised Depth Estimation, 3D Face Rotation and Replacement
Joel Ruben Antony Moniz, Christopher Beckham, Simon Rajotte, Sina Honari, Chris Pal
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Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs
Pedro Mercado, Francesco Tudisco, Matthias Hein
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