Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
In this paper we present lessons learned in the Evaluating Predictive Uncertainty Challenge. We describe the methods we used in regression challenges, including our winning method ...
The 1R procedure for machine learning is a very simple one that proves surprisingly effective on the standard datasets commonly used for evaluation. This paper describes the metho...
Craig G. Nevill-Manning, Geoffrey Holmes, Ian H. W...
We compare and contrast the strengths and weaknesses of a syntax-based machine translation model with a phrase-based machine translation model on several levels. We briefly descr...
Steve DeNeefe, Kevin Knight, Wei Wang 0006, Daniel...
This paper proposes a hybrid of handcrafted rules and a machine learning method for chunking Korean. In the partially free word-order languages such as Korean and Japanese, a smal...