Effects of Reduced Precision on Floating-Point SVM Classification Accuracy

Author:

Lesser Bernd,Mücke Manfred,Gansterer Wilfried N.

Publisher

Elsevier BV

Subject

General Engineering

Reference25 articles.

1. The nature of statistical learning theory;Vapnik,1995

2. M. Muecke, B. Lesser,W. N. Gansterer, Peak Performance Model for a Custom Precision Floating-Point Dot Product on FPGAs, ThirdWorkshop on UnConventional High Performance Computing 2010 (UCHPC 2010).(to appear in Lecture Notes in Computer Science, Springer-Verlag).

3. A digital architecture for support vector machines: theory, algorithm, and FPGA implementation, Neural Networks;Anguita;IEEE Transactions on,2003

4. T. Luo, L. Hall, D. Goldgof, A. Remsen, Bit reduction support vector machine, in: Data Mining, Fifth IEEE International Conference on, 2005, p. 4 pp.

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