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07/12/2023
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation
Generating unlabeled data has been recently shown to help address the fe...
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04/22/2023
Towards Understanding Feature Learning in Out-of-Distribution Generalization
A common explanation for the failure of out-of-distribution (OOD) genera...
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04/06/2023
SketchFFusion: Sketch-guided image editing with diffusion model
Sketch-guided image editing aims to achieve local fine-tuning of the ima...
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01/22/2023
Dance2MIDI: Dance-driven multi-instruments music generation
Dance-driven music generation aims to generate musical pieces conditione...
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08/21/2022
Combating Noisy-Labeled and Imbalanced Data by Two Stage Bi-Dimensional Sample Selection
Robust learning on noisy-labeled data has been an important task in real...
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06/15/2022
Pareto Invariant Risk Minimization
Despite the success of invariant risk minimization (IRM) in tackling the...
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06/14/2021
PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels
Semi-supervised node classification, as a fundamental problem in graph l...
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10/22/2020
Maximum Mean Discrepancy is Aware of Adversarial Attacks
The maximum mean discrepancy (MMD) test, as a representative two-sample ...
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10/05/2020
Pointwise Binary Classification with Pairwise Confidence Comparisons
Ordinary (pointwise) binary classification aims to learn a binary classi...
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02/10/2020
Towards Mixture Proportion Estimation without Irreducibility
Mixture proportion estimation (MPE) is a fundamental problem of practica...
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01/11/2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible
Learning with noisy labels has drawn a lot of attention. In this area, m...
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01/14/2019
