Ziyin Gu
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View article: On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation
On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Open
In this paper, we addressed the limitation of relying solely on distribution alignment and source-domain empirical risk minimization in Unsupervised Domain Adaptation (UDA). Our information-theoretic analysis showed that this standard adve…
View article: On the Generalization and Causal Explanation in Self-Supervised Learning
On the Generalization and Causal Explanation in Self-Supervised Learning Open
Self-supervised learning (SSL) methods learn from unlabeled data and achieve high generalization performance on downstream tasks. However, they may also suffer from overfitting to their training data and lose the ability to adapt to new ta…
View article: Table of Contents
Table of Contents Open