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Measuring Generalization with Optimal Transport
Understanding the generalization of deep neural networks is one of the m...
06/07/2021 ∙ by Ching-Yao Chuang, et al. ∙
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Fair Mixup: Fairness via Interpolation
Training classifiers under fairness constraints such as group fairness, ...
03/11/2021 ∙ by Ching-Yao Chuang, et al. ∙
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Contrastive Learning with Hard Negative Samples
We consider the question: how can you sample good negative examples for ...
10/09/2020 ∙ by Joshua Robinson, et al. ∙
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Estimating Generalization under Distribution Shifts via Domain-Invariant Representations
When machine learning models are deployed on a test distribution differe...
07/06/2020 ∙ by Ching-Yao Chuang, et al. ∙
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Debiased Contrastive Learning
A prominent technique for self-supervised representation learning has be...
07/01/2020 ∙ by Ching-Yao Chuang, et al. ∙
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The Role of Embedding Complexity in Domain-invariant Representations
Unsupervised domain adaptation aims to generalize the hypothesis trained...
10/13/2019 ∙ by Ching-Yao Chuang, et al. ∙
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Learning to Act Properly: Predicting and Explaining Affordances from Images
We address the problem of affordance reasoning in diverse scenes that ap...
12/20/2017 ∙ by Ching-Yao Chuang, et al. ∙
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Show, Adapt and Tell: Adversarial Training of Cross-domain Image Captioner
Impressive image captioning results are achieved in domains with plenty ...
05/02/2017 ∙ by Tseng-Hung Chen, et al. ∙
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Leveraging Video Descriptions to Learn Video Question Answering
We propose a scalable approach to learn video-based question answering (...
11/12/2016 ∙ by Kuo-Hao Zeng, et al. ∙
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