7 citations · 27 across the 13 of their papers we have counts for
13 papers
E2PL: Effective and Efficient Prompt Learning for Incomplete Multi-view Multi-Label Class Incremental Learning
Jiajun Chen, Yue Wu, Kai Huang +6
Multi-view multi-label classification (MvMLC) is indispensable for modern web applications aggregating information from diverse sources. However, real-world web-scale settings are…
TriSPrompt: A Hierarchical Soft Prompt Model for Multimodal Rumor Detection with Incomplete Modalities
Jiajun Chen, Yangyang Wu, Xiaoye Miao +2
The widespread presence of incomplete modalities in multimodal data poses a significant challenge to achieving accurate rumor detection. Existing multimodal rumor detection methods…
BPI: A Novel Efficient and Reliable Search Structure for Hybrid Storage Blockchain
Xinkui Zhao, Rengrong Xiong, Guanjie Cheng +7
Hybrid storage solutions have emerged as potent strategies to alleviate the data storage bottlenecks prevalent in blockchain systems. These solutions harness off-chain Storage Serv…
Delta: A Learned Mixed Cost-based Query Optimization Framework
Jiazhen Peng, Zheng Qu, Xiaoye Miao +1
Query optimizer is a crucial module for database management systems. Existing optimizers exhibit two flawed paradigms: (1) cost-based optimizers use dynamic programming with cost m…
ZeroED: Hybrid Zero-shot Error Detection through Large Language Model Reasoning
Wei Ni, Kaihang Zhang, Xiaoye Miao +4
Error detection (ED) in tabular data is crucial yet challenging due to diverse error types and the need for contextual understanding. Traditional ED methods often rely heavily on m…
Lossless Privacy-Preserving Aggregation for Decentralized Federated Learning
Xiaoye Miao, Bin Li, Yanzhang +2
Privacy concerns arise as sensitive data proliferate. Despite decentralized federated learning (DFL) aggregating gradients from neighbors to avoid direct data transmission, it stil…
Gradient Purification: Defense Against Poisoning Attack in Decentralized Federated Learning
Bin Li, Xiaoye Miao, Yan Zhang +1
Decentralized federated learning (DFL) is inherently vulnerable to data poisoning attacks, as malicious clients can transmit manipulated gradients to neighboring clients. Existing…
Automatic Data Repair: Are We Ready to Deploy?
Wei Ni, Xiaoye Miao, Xiangyu Zhao +2
Data quality is paramount in today's data-driven world, especially in the era of generative AI. Dirty data with errors and inconsistencies usually leads to flawed insights, unrelia…
Modern Data Pricing Models: Taxonomy and Comprehensive Survey
Xiaoye Miao, Huanhuan Peng, Xinyu Huang +3
Data play an increasingly important role in smart data analytics, which facilitate many data-driven applications. The goal of various data markets aims to alleviate the issue of is…
Differentiable and Scalable Generative Adversarial Models for Data Imputation
Yangyang Wu, Jun Wang, Xiaoye Miao +2
Data imputation has been extensively explored to solve the missing data problem. The dramatically increasing volume of incomplete data makes the imputation models computationally i…
Indexing Metric Spaces for Exact Similarity Search
Lu Chen, Yunjun Gao, Xuan Song +4
With the continued digitization of societal processes, we are seeing an explosion in available data. This is referred to as big data. In a research setting, three aspects of the da…
KGClean: An Embedding Powered Knowledge Graph Cleaning Framework
Congcong Ge, Yunjun Gao, Honghui Weng +3
The quality assurance of the knowledge graph is a prerequisite for various knowledge-driven applications. We propose KGClean, a novel cleaning framework powered by knowledge graph…
A Hybrid Data Cleaning Framework using Markov Logic Networks
Yunjun Gao, Congcong Ge, Xiaoye Miao +3
With the increase of dirty data, data cleaning turns into a crux of data analysis. Most of the existing algorithms rely on either qualitative techniques (e.g., data rules) or quant…