LGApr 3, 2012
The Kernelized Stochastic Batch Perceptron
arXiv:1204.0566v216 citations
AI Analysis
This addresses efficiency challenges in kernel SVM training for machine learning practitioners, though it appears incremental as it builds on existing optimization methods.
The paper tackles the problem of training kernel Support Vector Machines by presenting a novel approach with improved learning runtime guarantees compared to existing methods, and demonstrates its practical effectiveness in experiments.
We present a novel approach for training kernel Support Vector Machines, establish learning runtime guarantees for our method that are better then those of any other known kernelized SVM optimization approach, and show that our method works well in practice compared to existing alternatives.