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Mixed Bregman Clustering with Approximation Guarantees.

R. Nock, P. Luosto, и J. Kivinen. ECML/PKDD (2), том 5212 из Lecture Notes in Computer Science, стр. 154-169. Springer, (2008)

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Gaussian Clusters and Noise: An Approach Based on the Minimum Description Length Principle.P. Luosto, J. Kivinen, и H. Mannila. Discovery Science, том 6332 из Lecture Notes in Computer Science, стр. 251-265. Springer, (2010)Learning Hierarchical Rule Sets.J. Kivinen, H. Mannila, и E. Ukkonen. COLT, стр. 37-44. ACM, (1992)The Power of Sampling in Knowledge Discovery.J. Kivinen, и H. Mannila. PODS, стр. 77-85. ACM Press, (1994)Online Learning of Linear Classifiers.J. Kivinen. Machine Learning Summer School, том 2600 из Lecture Notes in Computer Science, стр. 235-258. Springer, (2002)Attribute-Efficient Learning.J. Kivinen. Encyclopedia of Algorithms, Springer, (2008)Worst-case Loss Bounds for Single Neurons.D. Helmbold, J. Kivinen, и M. Warmuth. NIPS, стр. 309-315. MIT Press, (1995)Averaging Expert PredictionsJ. Kivinen, и M. Warmuth. EuroCOLT, том 1572 из Lecture Notes in Computer Science, стр. 153-167. Springer, (1999)Using experts for predicting continuous outcomes.J. Kivinen, и M. Warmuth. EuroCOLT, стр. 109-120. Oxford University Press, (1993)Reliable and Useful Learning.J. Kivinen. COLT, стр. 365-380. Morgan Kaufmann, (1989)Boosting as Entropy Projection.J. Kivinen, и M. Warmuth. COLT, стр. 134-144. ACM, (1999)