Abstract. We address the problem of joint feature selection in multiple related classification or regression tasks. When doing feature selection with multiple tasks, usually one c...
Paramveer S. Dhillon, Brian Tomasik, Dean P. Foste...
- In this paper we propose a new methodology for Cost-Benefit analysis in a multiple time series prediction problem. The proposed model is evaluated in a real world application bas...
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, th...