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07/04/2023
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis
Trustworthy deployment of deep learning medical imaging models into real...
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03/06/2023
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis
Although deep learning (DL) models have shown great success in many medi...
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11/15/2022
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors
We propose a hierarchically structured variational inference model for a...
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10/19/2022
On Learning Fairness and Accuracy on Multiple Subgroups
We propose an analysis in fair learning that preserves the utility of th...
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08/01/2022
Information Gain Sampling for Active Learning in Medical Image Classification
Large, annotated datasets are not widely available in medical image anal...
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05/26/2022
Fair Representation Learning through Implicit Path Alignment
We consider a fair representation learning perspective, where optimal pr...
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09/29/2021
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis
We derive a novel information-theoretic analysis of the generalization p...
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05/30/2021
On the benefits of representation regularization in invariance based domain generalization
A crucial aspect in reliable machine learning is to design a deployable ...
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05/09/2021
Aggregating From Multiple Target-Shifted Sources
Multi-source domain adaptation aims at leveraging the knowledge from mul...
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11/07/2020
Interventional Domain Adaptation
Domain adaptation (DA) aims to transfer discriminative features learned ...
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07/30/2020
Beyond ℋ-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence
We reveal the incoherence between the widely-adopted empirical domain ad...
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07/21/2020
Domain Generalization with Optimal Transport and Metric Learning
Generalizing knowledge to unseen domains, where data and labels are unav...
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05/24/2020
Discriminative Active Learning for Domain Adaptation
Domain Adaptation aiming to learn a transferable feature between differe...
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11/20/2019
Deep Active Learning: Unified and Principled Method for Query and Training
In this paper, we proposed a unified and principled method for both quer...
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10/18/2019
Toward Metrics for Differentiating Out-of-Distribution Sets
Vanilla CNNs, as uncalibrated classifiers, suffer from classifying out-o...
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03/21/2019
A Principled Approach for Learning Task Similarity in Multitask Learning
Multitask learning aims at solving a set of related tasks simultaneously...
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10/26/2018
Accumulating Knowledge for Lifelong Online Learning
Lifelong learning can be viewed as a continuous transfer learning proced...
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02/22/2018
