Search Results for author: Jingzhi Guo

Found 3 papers, 1 papers with code

AIDA: Legal Judgment Predictions for Non-Professional Fact Descriptions via Partial-and-Imbalanced Domain Adaptation

no code implementations12 Feb 2023 Guangyi Xiao, Xinlong Liu, Hao Chen, Jingzhi Guo, Zhiguo Gong

In this paper, we study the problem of legal domain adaptation problem from an imbalanced source domain to a partial target domain.

Unsupervised Domain Adaptation

NI-UDA: Graph Adversarial Domain Adaptation from Non-shared-and-Imbalanced Big Data to Small Imbalanced Applications

no code implementations11 Aug 2021 Guangyi Xiao, Weiwei Xiang, Huan Liu, Hao Chen, Shun Peng, Jingzhi Guo, Zhiguo Gong

We propose a new general Graph Adversarial Domain Adaptation (GADA) based on semantic knowledge reasoning of class structure for solving the problem of unsupervised domain adaptation (UDA) from the big data with non-shared and imbalanced classes to specified small and imbalanced applications (NI-UDA), where non-shared classes mean the label space out of the target domain.

Unsupervised Domain Adaptation

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