Dmitriy Panchenko, Ph.D.

Affiliations: 
2002 University of New Mexico, Albuquerque, NM, United States 
Area:
Mathematics
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"Dmitriy Panchenko"

Parents

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Vladimir Koltchinskii grad student 2002 Univ. of New Mexico
 (Concentration inequalities in product spaces and applications to statistical learning theory.)
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Publications

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Conti A, Panchenko D, Sidenko S, et al. (2009) Log-concavity property of the error probability with application to local bounds for wireless communications Ieee Transactions On Information Theory. 55: 2766-2775
Koltchinskii V, Panchenko D. (2005) Complexities of convex combinations and bounding the generalization error in classification Annals of Statistics. 33: 1455-1496
Koltchinskii V, Panchenko D, Andonova S. (2003) Generalization bounds for voting classifiers based on sparsity and clustering Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 2777: 492-505
Koltchinskii V, Panchenko D, Lozano F. (2003) Bounding the generalization error of convex combinations of classifiers: Balancing the dimensionality and the margins Annals of Applied Probability. 13: 213-252
Koltchinskii V, Panchenko D. (2002) Empirical margin distributions and bounding the generalization error of combined classifiers Annals of Statistics. 30: 1-50
Bousquet O, Koltchinskii V, Panchenko D. (2002) Some local measures of complexity of convex hulls and generalization bounds Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 2375: 59-73
Koltchinskii V, Panchenko D, Lozano F. (2001) Further explanation of the effectiveness of voting methods: The game between margins and weights Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2111: 241-255
Koltchinskii V, Panchenko D, Lozano F. (2001) Some new bounds on the generalization error of combined classifiers Advances in Neural Information Processing Systems
Koltchinskii V, Abdallah CT, Ariola M, et al. (2000) Improved sample complexity estimates for statistical learning control of uncertain systems Ieee Transactions On Automatic Control. 45: 2383-2388
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