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This paper presents the ongoing research on the GPU SVM solutions for classification of big sparse datasets. In particular, after the success of implementation of RBF kernel for sparse matrix formats in previous work we decided to evaluate Chi$^{2}$ and Exponential Chi$^{2}$ kernels. Moreover, the details of GPU solver are pointed. Experimental session summarizes results of GPU SVM classification for different sparse data formats and different SVM kernels and demonstrates that solution for Exponential Chi$^2$ achieves significant accelerations in GPU SVM processing, while the results for Chi$^2$ kernel are very far from satisfactory.

GPU Solver with Chi-square Kernels for SVM Classification of Big Sparse Problems