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» Learning Models for Predicting Recognition Performance
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105
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TNN
2010
173views Management» more  TNN 2010»
14 years 9 months ago
Multiclass relevance vector machines: sparsity and accuracy
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...
BMCBI
2006
119views more  BMCBI 2006»
15 years 2 months ago
Hidden Markov Model Variants and their Application
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...
Stephen Winters-Hilt
132
Voted
IJCNN
2007
IEEE
15 years 9 months ago
A Constructive-Fuzzy System Modeling for Time Series Forecasting
— 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...
Ivette Luna, Secundino Soares, Rosangela Ballini
111
Voted
TCIAIG
2010
14 years 9 months ago
Modeling Player Experience for Content Creation
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....
111
Voted
ICASSP
2011
IEEE
14 years 6 months ago
Time-evolving modeling of social networks
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 ...