2 citations · 3 across the 9 of their papers we have counts for
11 papers
MERIT: Efficient In-Place Deletion for Dynamic Graph-Based Approximate Nearest Neighbor Indexes
Zekai Wu, Jiabao Jin, Peng Cheng +6
Graph-based indexes have become the dominant approach to approximate nearest neighbor search (ANNS) over high-dimensional data and play a crucial role in real-world applications su…
Personalized w-Event Privacy for Infinite Stream Estimation
Leilei Du, Xu Zhou, Peng Cheng +4
In applications such as event monitoring, log analysis, and video querying, -event privacy protects individual data within a sliding time window while supporting accurate stream…
FGIM: a Fast Graph-based Indexes Merging Framework for Approximate Nearest Neighbor Search
Zekai Wu, Jiabao Jin, Peng Cheng +7
As the state-of-the-art methods for high-dimensional data retrieval, Approximate Nearest Neighbor Search (ANNS) approaches with graph-based indexes have attracted increasing attent…
Approximate Nearest Neighbor Search of Large Scale Vectors on Distributed Storage
Kun Yu, Jiabao Jin, Xiaoyao Zhong +6
Approximate Nearest Neighbor Search (ANNS) in high-dimensional space is an essential operator in many online services, such as information retrieval and recommendation. Indices con…
Infinite Stream Estimation under Personalized -Event Privacy
Leilei Du, Peng Cheng, Lei Chen +3
Streaming data collection is indispensable for stream data analysis, such as event monitoring. However, publishing these data directly leads to privacy leaks. -event privacy is…
ContextCache: Context-Aware Semantic Cache for Multi-Turn Queries in Large Language Models
Jianxin Yan, Wangze Ni, Lei Chen +4
Semantic caching significantly reduces computational costs and improves efficiency by storing and reusing large language model (LLM) responses. However, existing systems rely prima…
EnhanceGraph: A Continuously Enhanced Graph-based Index for High-dimensional Approximate Nearest Neighbor Search
Xiaoyao Zhong, Jiabao Jin, Peng Cheng +5
Recently, Approximate Nearest Neighbor Search in high-dimensional vector spaces has garnered considerable attention due to the rapid advancement of deep learning techniques. We obs…
Efficient Multiple Temporal Network Kernel Density Estimation
Yu Shao, Peng Cheng, Xiang Lian +5
Kernel density estimation (KDE) has become a popular method for visual analysis in various fields, such as financial risk forecasting, crime clustering, and traffic monitoring. KDE…
Numerical Estimation of Spatial Distributions under Differential Privacy
Leilei Du, Peng Cheng, Libin Zheng +4
Estimating spatial distributions is important in data analysis, such as traffic flow forecasting and epidemic prevention. To achieve accurate spatial distribution estimation, the a…
StructRide: A Framework to Exploit the Structure Information of Shareability Graph in Ridesharing
Jiexi Zhan, Yu Chen, Peng Cheng +3
Ridesharing services play an essential role in modern transportation, which significantly reduces traffic congestion and exhaust pollution. In the ridesharing problem, improving th…
Wait to be Faster: a Smart Pooling Framework for Dynamic Ridesharing
Xiaoyao Zhong, Jiabao Jin, Peng Cheng +4
Ridesharing services, such as Uber or Didi, have attracted considerable attention in recent years due to their positive impact on environmental protection and the economy. Existing…