2 citations · 4 across the 5 of their papers we have counts for
5 papers
Sensitivity estimation for differentially private query processing
Meifan Zhang, Xin Liu, Lihua Yin
Differential privacy has become a popular privacy-preserving method in data analysis, query processing, and machine learning, which adds noise to the query result to avoid leaking…
Local Differentially Private Frequency Estimation based on Learned Sketches
Meifan Zhang, Sixin Lin, Lihua Yin
Sketches are widely used for frequency estimation of data with a large domain. However, sketches-based frequency estimation faces more challenges when considering privacy. Local di…
Approximate Query Processing for Group-By Queries based on Conditional Generative Models
Meifan Zhang, Hongzhi Wang
The Group-By query is an important kind of query, which is common and widely used in data warehouses, data analytics, and data visualization. Approximate query processing is an eff…
LAQP: Learning-based Approximate Query Processing
Meifan Zhang, Hongzhi Wang
Querying on big data is a challenging task due to the rapid growth of data amount. Approximate query processing (AQP) is a way to meet the requirement of fast response. In this pap…
Diversification on Big Data in Query Processing
Meifan Zhang, Hongzhi Wang, Jianzhong Li +1
Recently, in the area of big data, some popular applications such as web search engines and recommendation systems, face the problem to diversify results during query processing. I…