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Posts by Collection
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publications
Deep into The Domain Shift: Transfer Learning through Dependence Regularization
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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Network Vector Autoregressive Moving Average Model
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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A Unified Domain Adaptation Framework with Distinctive Divergence Analysis
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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On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective
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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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
SDSC2001 Python for Data Science (Fall 2021)
Undergraduate course, City University of Hong Kong, School of Data Science, 2021
Teacher: Prof. Xinyue Li
SDSC2003 Human Contexts & Eths in DS (Spring 2022)
Undergraduate course, City University of Hong Kong, School of Data Science, 2022
Teacher: Prof. Linyan Li
SDSC6013 Topics in Fin Eng & Tech
Postgraduate course, City University of Hong Kong, School of Data Science, 2023
Teacher: Prof. Qi Wu