Search Results - "Vapnik, V."

Complete Statistical Theory of Learning by Vapnik, V. N.

“…Existing mathematical model of learning requires using training data find in a given subset of admissible function the function that minimizes the expected…”
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Bounds on error expectation for support vector machines by Vapnik, V, Chapelle, O

“…We introduce the concept of span of support vectors (SV) and show that the generalization ability of support vector machines (SVM) depends on this new…”
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Comparing support vector machines with Gaussian kernels to radial basis function classifiers by Scholkopf, B., Kah-Kay Sung, Burges, C.J.C., Girosi, F., Niyogi, P., Poggio, T., Vapnik, V.

“…The support vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural…”
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What size test set gives good error rate estimates? by Guyon, I., Makhoul, J., Schwartz, R., Vapnik, V.

“…We address the problem of determining what size test set guarantees statistically significant results in a character recognition task, as a function of the…”
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Comparison of classifier methods: a case study in handwritten digit recognition by Bottou, L., Cortes, C., Denker, J.S., Drucker, H., Guyon, I., Jackel, L.D., LeCun, Y., Muller, U.A., Sackinger, E., Simard, P., Vapnik, V.

“…This paper compares the performance of several classifier algorithms on a standard database of handwritten digits. We consider not only raw accuracy, but also…”
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An overview of statistical learning theory by Vapnik, V.N.

“…Statistical learning theory was introduced in the late 1960's. Until the 1990's it was a purely theoretical analysis of the problem of function estimation from…”
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Melilite-olivine neрhelinites of Mt. Tabaat (Makhtesh Ramon, Israel): Geological, petrographic and geochemical characteristics and conditions of genesis by Yudalevich, Z. A., Vapnik, V. A., Vishnyakova, M. D., Borodina, N. S.

“…Research subject. The melilite-olivine nephelinite subvolcanic body Tabaat, which includes melilite rocks found for the first time on the territory of Levant…”
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Support vector machines for histogram-based image classification by Chapelle, O., Haffner, P., Vapnik, V.N.

“…Traditional classification approaches generalize poorly on image classification tasks, because of the high dimensionality of the feature space. This paper…”
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Support vector machines for spam categorization by Drucker, H., Donghui Wu, Vapnik, V.N.

“…We study the use of support vector machines (SVM) in classifying e-mail as spam or nonspam by comparing it to three other classification algorithms: Ripper,…”
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Model complexity control for regression using VC generalization bounds by Cherkassky, V., Xuhui Shao, Mulier, F.M., Vapnik, V.N.

“…It is well known that for a given sample size there exists a model of optimal complexity corresponding to the smallest prediction (generalization) error…”
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SVM method of estimating density, conditional probability, and conditional density by Vapnik, V.

“…The problem of estimating density, conditional probability, and conditional density is considered as an ill-posed problem of solving integral equations. To…”
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Learning hidden information: SVM by Vapnik, V.

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Learning using hidden information (Learning with teacher) by Vapnik, V., Vashist, A., Pavlovitch, N.

“…In this paper we consider a new paradigm of learning: learning using hidden information. The classical paradigm of the supervised learning is to learn a…”
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Empirical inference problems by Vapnik, V.

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A support vector clustering method by Ben-Hur, A., Horn, D., Siegelmann, H.T., Vapnik, V.

“…We present a novel kernel method for data clustering using a description of the data by support vectors. The kernel reflects a projection of the data points…”
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Comparing support vector machines with Gaussian kernels to radial basis function classifiers: Neural networks by SCHÖLKOPF, B, SUNG, K.-K, BURGES, C. J. C, GIROSI, F, NIYOGI, P, POGGIO, T, VAPNIK, V

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An overview of statistical learning theory : Vapnik-Chervonekis (VC) learning theory and its applications by VAPNIK, V. N

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Computer aided cleaning of large databases for character recognition by Matic, N., Guyon, I., Bottou, L., Denker, J., Vapnik, V.

“…A method for computer-aided cleaning of undesirable patterns in large training databases has been developed. The method uses the trainable classifier itself,…”
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Support vector machines for histogram-based image classification : Vapnik-Chervonekis (VC) learning theory and its applications by CHAPELLE, O, HAFFNER, P, VAPNIK, V. N

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Capacity control in linear classifiers for pattern recognition by Guyon, I., Vapnik, V., Boser, B., Bottou, L., Solla, S.A.

“…Achieving good performance in statistical pattern recognition requires matching the capacity of the classifier to the amount of training data. If the…”
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