Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
The usefulness of the results produced by data mining methods can be critically impaired by several factors such as (1) low quality of data, including errors due to contamination, ...
Fang Chu, Yizhou Wang, Carlo Zaniolo, Douglas Stot...
The Noise Sensitivity Signature (NSS), originally introduced by Grossman and Lapedes (1993), was proposed as an alternative to cross validation for selecting network complexity. I...
This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
It is difficult for instructors of CS1 and CS2 courses to get accurate answers to such critical questions as "how long are students spending on programming assignments?"...
Christian Murphy, Gail E. Kaiser, Kristin Loveland...