Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
This paper presents a method for updating approximations of a concept incrementally. The results can be used to implement a quasi-incremental algorithm for learning classification...
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...
The field of transfer learning aims to speed up learning across multiple related tasks by transferring knowledge between source and target tasks. Past work has shown that when th...
Objects linking with many other objects in an information network may imply various semantic relationships. Uncovering such knowledge is essential for role discovery, data cleanin...
Chi Wang, Jiawei Han, Qi Li, Xiang Li, Wen-Pin Lin...