Chang MW, Lin CJ. (2005). Leave-One-Out Bounds for Support Vector Regression Model Selection Neural Comput. 17
Gunter L, Zhu J. (2007). Efficient computation and model selection for the support vector regression. Neural computation. 19 [PubMed]
Kao WC, Chung KM, Sun CL, Lin CJ. (2004). Decomposition Methods for Linear Support Vector Machines Neural Comput. 16
Knebel T, Hochreiter S, Obermayer K. (2008). An SMO algorithm for the potential support vector machine. Neural computation. 20 [PubMed]
Zhong M et al. (2007). Gap-based estimation: choosing the smoothing parameters for probabilistic and general regression neural networks. Neural computation. 19 [PubMed]