LGAug 17, 2013
Comment on "robustness and regularization of support vector machines" by H. Xu, et al., (Journal of Machine Learning Research, vol. 10, pp. 1485-1510, 2009, arXiv:0803.3490)
arXiv:1308.3750v11 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental critique that challenges a specific theoretical claim in machine learning robustness.
The paper addresses a theorem by Xu et al. that links robustness in feature and sample spaces for support vector machines, and provides a counterexample that disproves this theorem.
This paper comments on the published work dealing with robustness and regularization of support vector machines (Journal of Machine Learning Research, vol. 10, pp. 1485-1510, 2009) [arXiv:0803.3490] by H. Xu, etc. They proposed a theorem to show that it is possible to relate robustness in the feature space and robustness in the sample space directly. In this paper, we propose a counter example that rejects their theorem.