Title :
A VLSI friendly algorithm for support vector machines
Author :
Anguita, D. ; Boni, A. ; Ridella, S.
Author_Institution :
Dept. of Biophys, & Electron. Eng., Genova Univ., Italy
Abstract :
We propose a VLSI friendly algorithm for the implementation of the learning phase of support vector machines (SVM). Differently from previous methods, that rely on sophisticated constrained nonlinear programming algorithms, our approach finds a simple updating rule that can be easily implemented in digital VLSI
Keywords :
VLSI; digital integrated circuits; learning (artificial intelligence); neural nets; SVM; VLSI friendly algorithm; digital VLSI; learning phase; support vector machines; updating rule; Differential equations; Ear; Educational institutions; Kernel; Linear programming; Machine learning; Solids; Statistical learning; Support vector machines; Very large scale integration;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.831079
