Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
— This paper suggests a constructive fuzzy system modeling for time series prediction. The model proposed is based on Takagi-Sugeno system and it comprises two phases. First, a f...
In this paper, we use computational intelligence techniques to built quantitative models of player experience for a platform game. The models accurately predict certain key affecti...
Christopher Pedersen, Julian Togelius, Georgios N....
A statistical framework for modeling and prediction of binary matrices is presented. The method is applied to social network analysis, specifically the database of US Supreme Cou...
Eric Wang, Jorge Silva, Rebecca Willett, Lawrence ...