A support vector machine with integer parameters

作者：Angulta Davide; Ghio Alessandro^*; Pischiutta Stefano; Ridella Sandro

来源：Neurocomputing, 2008, 72(1-3): 480-489.

DOI：10.1016/j.neucom.2007.12.006

• Support vector machine (SVM)
• Mixed integer quadratic programming (MIQP)
• Branch-and-bound
• Sequential minimal optimization (SMO)
• Resource-limited hardware
• Sensor networks

We describe here a method for building a support vector machine (SVM) with integer parameters. Our method is based on a branch-and-bound procedure, derived from modern mixed integer quadratic programming solvers, and is useful for implementing the feed-forward phase of the SVM in fixed-point arithmetic. This allows the implementation of the SVM algorithm on resource-limited hardware like, for example, computing devices used for building sensor networks, where floating-point units are rarely available. The experimental results on well-known benchmarking data sets and a real-world people-detection application show the effectiveness of our approach.

• 出版日期2008-12