6 papers
LLMs Meet Isolation Kernel: Lightweight, Learning-free Binary Embeddings for Fast Retrieval
Zhibo Zhang, Yang Xu, Kai Ming Ting +1
Large language models (LLMs) have recently enabled remarkable progress in text representation. However, their embeddings are typically high-dimensional, leading to substantial stor…
SCoNE: Spherical Consistent Neighborhoods Ensemble for Effective and Efficient Multi-View Anomaly Detection
Yang Xu, Hang Zhang, Yixiao Ma +2
The core problem in multi-view anomaly detection is to represent local neighborhoods of normal instances consistently across all views. Recent approaches consider a representation…
IDK-S: Incremental Distributional Kernel for Streaming Anomaly Detection
Yang Xu, Yixiao Ma, Kaifeng Zhang +2
Anomaly detection on data streams presents significant challenges, requiring methods to maintain high detection accuracy among evolving distributions while ensuring real-time effic…
GeoPTH: A Lightweight Approach to Category-Based Trajectory Retrieval via Geometric Prototype Trajectory Hashing
Yang Xu, Zuliang Yang, Kai Ming Ting
Trajectory similarity retrieval is an important part of spatiotemporal data mining, however, existing methods have the following limitations: traditional metrics are computationall…
Contrastive Multi-View Graph Hashing
Yang Xu, Zuliang Yang, Kai Ming Ting
Multi-view graph data, which both captures node attributes and rich relational information from diverse sources, is becoming increasingly prevalent in various domains. The effectiv…
Voronoi Diagram Encoded Hashing
Yang Xu, Kai Ming Ting
The goal of learning to hash (L2H) is to derive data-dependent hash functions from a given data distribution in order to map data from the input space to a binary coding space. Des…