Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Building an accurate emerging pattern classifier with a highdimensional dataset is a challenging issue. The problem becomes even more difficult if the whole feature space is unava...
Kui Yu, Wei Ding 0003, Dan A. Simovici, Xindong Wu
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is sem...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...