LibMI: An Open Source Library for Efficient Histopathological Image Processing.
Yuxin Dong, Pargorn Puttapirat, Jingyi Deng, Xiangrong Zhang, Chen Li. Journal of Pathology Informatics. 2020. [Link] [PDF] [Code]
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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
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A Representation Model for Biological Entities by Fusing Structured Axioms with Unstructured Texts.
Peiliang Lou, Yuxin Dong, Antonio Jimeno Yepes, Chen Li. Bioinformatics. 2021. [Link] [PDF] [Code]
Regularized Modal Regression on Markov-Dependent Observations: A Theoretical Assessment.
Tieliang Gong, Yuxin Dong, Hong Chen, Wei Feng, Bo Dong, Chen Li. AAAI Conference on Artificial Intelligence. 2022. [Link] [PDF]
Markov Subsampling Based on Huber Criterion.
Tieliang Gong, Yuxin Dong, Hong Chen, Bo Dong, Chen Li. IEEE Transactions on Neural Networks and Learning Systems. 2022. [Link] [PDF]
Computationally Efficient Approximations for Matrix-Based Rényi's Entropy.
Tieliang Gong*, Yuxin Dong*, Shujian Yu, Bo Dong. IEEE Transactions on Signal Processing. 2022. [Link] [PDF]
Robust and Fast Measure of Information via Low-Rank Representation.
Yuxin Dong, Tieliang Gong, Shujian Yu, Hong Chen, Chen Li. AAAI Conference on Artificial Intelligence. 2023. [Link] [PDF] [Code]
Dual Attention and Patient Similarity Network for Drug Recommendation.
Jialun Wu, Yuxin Dong, Zeyu Gao, Tieliang Gong, and Chen Li. Bioinformatics. 2023. [Link] [PDF] [Code]
Understanding the Generalization Ability of Deep Learning Algorithms: A Kernelized Rényi’s Entropy Perspective.
Yuxin Dong, Tieliang Gong, Hong Chen, Chen Li. International Joint Conference on Artificial Intelligence. 2023. [Link] [PDF] [Code]
Optimal Randomized Approximations for Matrix-based Rényi's Entropy.
Yuxin Dong, Tieliang Gong, Shujian Yu, Chen Li. IEEE Transactions on Information Theory. 2023. [Link] [PDF]
Efficient Approximations for Matrix-Based Rényi’s Entropy on Sequential Data.
Yuxin Dong, Tieliang Gong, Hong Chen, Chen Li. IEEE Transactions on Neural Networks and Learning Systems. 2023. [Link] [PDF]
Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds.
Yuxin Dong, Tieliang Gong, Hong Chen, Shujian Yu, Chen Li. International Conference on Learning Representations. 2024. [Link] [PDF] [Code]
Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective.
Yuxin Dong, Tieliang Gong, Hong Chen, Mengxiang Li, Zhongjiang He, Shuangyong Song, Chen Li. International Conference on Machine Learning. 2024. [Link] [PDF] [Code]
Information-theoretic Generalization Analysis for Randomized Learning Algorithms.
Yuxin Dong. PhD Thesis. 2024. [Link] [PDF]
How Does Distribution Matching Help Domain Generalization: An Information-theoretic Analysis.
Yuxin Dong, Tieliang Gong, Hong Chen, Shuangyong Song, Weizhan Zhang, Chen Li. IEEE Transactions on Information Theory. 2025. [Link] [PDF]