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05/19/2023
Enriching Disentanglement: Definitions to Metrics
Disentangled representation learning is a challenging task that involves...
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05/11/2023
A Category-theoretical Meta-analysis of Definitions of Disentanglement
Disentangling the factors of variation in data is a fundamental concept ...
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08/03/2022
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift
Machine learning systems may encounter unexpected problems when the data...
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03/25/2021
Approximating Instance-Dependent Noise via Instance-Confidence Embedding
Label noise in multiclass classification is a major obstacle to the depl...
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02/04/2021
Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization
Many weakly supervised classification methods employ a noise transition ...
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10/22/2020
Classification with Rejection Based on Cost-sensitive Classification
The goal of classification with rejection is to avoid risky misclassific...
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04/14/2020
Learning from Aggregate Observations
We study the problem of learning from aggregate observations where super...
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10/10/2019