Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
Most research in learning for planning has concentrated on efficiency gains. Another important goal is improving the quality of final plans. Learning to improve plan quality has b...
In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such mode...