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Found 3 papers, 1 papers with code
AIDA: Legal Judgment Predictions for Non-Professional Fact Descriptions via Partial-and-Imbalanced Domain Adaptation
In this paper, we study the problem of legal domain adaptation problem from an imbalanced source domain to a partial target domain.
BiC-Net: Learning Efficient Spatio-Temporal Relation for Text-Video Retrieval
The task of text-video retrieval aims to understand the correspondence between language and vision, has gained increasing attention in recent years.
NI-UDA: Graph Adversarial Domain Adaptation from Non-shared-and-Imbalanced Big Data to Small Imbalanced Applications
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.
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