3 papers
cs.IR2026
Approximate Nearest Neighbor Search for Modern AI: A Projection-Augmented Graph Approach
Kejing Lu, Zhenpeng Pan, Jianbin Qin +2
Approximate Nearest Neighbor Search (ANNS) is fundamental to modern AI applications. Most existing solutions optimize query efficiency but fail to align with the practical requirem…
cs.LG2025
Probabilistic Kernel Function for Fast Angle Testing
Kejing Lu, Chuan Xiao, Yoshiharu Ishikawa
In this paper, we study the angle testing problem in the context of similarity search in high-dimensional Euclidean spaces and propose two projection-based probabilistic kernel fun…
cs.LG2024
Probabilistic Routing for Graph-Based Approximate Nearest Neighbor Search
Kejing Lu, Chuan Xiao, Yoshiharu Ishikawa
Approximate nearest neighbor search (ANNS) in high-dimensional spaces is a pivotal challenge in the field of machine learning. In recent years, graph-based methods have emerged as…