Kernels as features: On kernels, margins, and low-dimensional mappings

Author:

Balcan Maria-Florina,Blum Avrim,Vempala Santosh

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference27 articles.

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2. Arriaga, R. I., & Vempala, S. (1999). An algorithmic theory of learning, robust concepts and random projection. Proceedings of the 40th foundations of computer science. Journal version to appear in Machine Learning, 616–623.

3. Bartlett, P., & Shawe-Taylor, J. (1999). Generalization performance of support vector machines and other pattern classifiers. Advances in kernel methods: Support vector learning (pp. 43–54). MIT Press.

4. Ben-David, S., Eiron, N., & Simon, H.U. (2003). Limitations of learning via embeddings in euclidean half-spaces Journal of Machine Learning Research, 3, 441–461.

5. Ben-David, S. (2001). A priori generalization bounds for kernel based learning. NIPS Workshop on kernel based learning.

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