In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
Abstract. There are many connections between graph mining and inductive logic programming (ILP), or more generally relational learning. Up till now these connections have mostly be...
Recovering design patterns applied in a system can help refactoring the system. Machine learning algorithms have been successfully applied in mining data patterns. However, one of...
The error-correcting output coding (ECOC) method reduces the multiclass learning problem into a series of binary classifiers. In this paper, we consider the dense ECOC methods, co...
Aijun Zhang, Zhi-Li Wu, Chun Hung Li, Kai-Tai Fang
It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, ...