In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
As we devise more complicated prior distributions, will inference algorithms keep up? We highlight a negative result in computable probability theory by Ackerman, Freer, and Roy (...
Supervised learning on sequence data, also known as sequence classification, has been well recognized as an important data mining task with many significant applications. Since te...
Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. ...
Much of artificial intelligence research is focused on devising optimal solutions for challenging and well-defined but highly constrained problems. However, as we begin creating...
The application of AI planning techniques to manufacturing systems is being widely deployed for all the tasks involved in the process, from product design to production planning an...