Figure 7

Comparison of QP formulation and SIP formulation on large scale data. Comparison of QP formulation and SIP formulation on large scale data. Figure on the top left: comparison of SOCP and QCQP formulations to solve 1-SVM MKL using two kernels. To simulate the ranking problem in 1-SVM, 3000 digit samples were retrieved as training data. Two kernels were constructed respectively for each data source using RBF kernel functions. The computational time was thus evaluated by combining the two 3000 × 3000 kernel matrices. Figure on the top right: comparison of SVM and LSSVM MKL on problems with increasing number of samples. The benchmark data set was made up of two linear kernels and labels in 10 digit classes. The number of data points was increased from 1000 to 3000. Figure on the bottom left: comparison of SVM and LSSVM MKL on problems with increasing number of kernels. The benchmark data set was constructed by 2000 samples labeled in 2 classes. We used different kernel widths to construct the RBF kernel matrices and increase the number of kernel matrices from 2 to 200. The QCQP formulations had memory issues when the number of kernels was larger than 60. Figure on the bottom right: comparison of SVM and LSSVM on problems with increasing number of classes. The benchmark data was made up of two linear kernel matrices and 2000 samples. The samples were equally and randomly divided into various number of classes. The class number gradually increased from 2 to 20.