In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
One of the main challenges in content-based image retrieval still remains to bridge the gap between low-level features and semantic information. In this paper, we present our first...
Daniel Racoceanu, Caroline Lacoste, Roxana Teodore...
We consider the problem of ordinal classification, in which a value set of the decision attribute (output, dependent variable) is finite and ordered. This problem shares some chara...
Krzysztof Dembczynski, Wojciech Kotlowski, Roman S...
Gene Expression Programming (GEP) aims at discovering essential rules hidden in observed data and expressing them mathematically. GEP has been proved to be a powerful tool for cons...
Lei Duan, Changjie Tang, Tianqing Zhang, Dagang We...
— Our work explores the use of several text categorization techniques for classification of manufacturing quality defect and service shop data sets into fixed categories. Althoug...