Published in arxiv, 2023
We systematically study and evaluate the adversarial robustness and out-of-distribution generalization of ChatGPT and other large language models in this article.
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Published in Transactions on Machine Learning Research, 2022
In this paper, we propose a unified framework that provides a shared understanding of both domain adaptation problems, including classification and regression, from the same perspective.
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Published in Statistics and Its Interface, 2022
In this paper, we propose a NARMA model that integrates both the autoregressive and moving average components into the network models.
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Published in SSRN, 2022
In this papaer, we develop a novel domain adaptation method that can flexibly model the correspondence strength between source distributions and target distributions.
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