Online learning with kernels J Kivinen, AJ Smola, RC Williamson Signal Processing, IEEE Transactions on 52 (8), 2165-2176, 2004 | 1228 | 2004 |
Online learning with kernels J Kivinen, AJ Smola, RC Williamson Advances in neural information processing systems 1, 785-792, 2002 | 1228 | 2002 |
Exponentiated gradient versus gradient descent for linear predictors J Kivinen, MK Warmuth information and computation 132 (1), 1-63, 1997 | 1138* | 1997 |
Approximate inference of functional dependencies from relations J Kivinen, H Mannila Theoretical Computer Science 149 (1), 129-149, 1995 | 263 | 1995 |
Sequential prediction of individual sequences under general loss functions D Haussler, J Kivinen, MK Warmuth IEEE Transactions on Information Theory 44 (5), 1906-1925, 1998 | 204 | 1998 |
Relative loss bounds for multidimensional regression problems J Kivinen, MKK Warmuth Advances in neural information processing systems 10, 1997 | 186 | 1997 |
The Perceptron algorithm versus Winnow: linear versus logarithmic mistake bounds when few input variables are relevant J Kivinen, MK Warmuth, P Auer Artificial Intelligence 97 (1-2), 325-343, 1997 | 185 | 1997 |
The power of sampling in knowledge discovery J Kivinen, H Mannila Proceedings of the thirteenth ACM SIGACT-SIGMOD-SIGART symposium on …, 1994 | 179 | 1994 |
Averaging expert predictions J Kivinen, MK Warmuth European Conference on Computational Learning Theory, 153-167, 1999 | 168 | 1999 |
Boosting as entropy projection J Kivinen, MK Warmuth Proceedings of the twelfth annual conference on Computational learning …, 1999 | 156 | 1999 |
Additive versus exponentiated gradient updates for linear prediction J Kivinen, MK Warmuth Proceedings of the twenty-seventh annual ACM symposium on Theory of …, 1995 | 133 | 1995 |
Approximate dependency inference from relations J Kivinen, H Mannila International Conference on Database Theory, 86-98, 1992 | 124 | 1992 |
Tight worst-case loss bounds for predicting with expert advice D Haussler, J Kivinen, MK Warmuth European Conference on Computational Learning Theory, 69-83, 1995 | 113 | 1995 |
Hedging Structured Concepts. WM Koolen, MK Warmuth, J Kivinen COLT, 93-105, 2010 | 109 | 2010 |
Relative loss bounds for single neurons DP Helmbold, J Kivinen, MK Warmuth Neural Networks, IEEE Transactions on 10 (6), 1291-1304, 1999 | 95* | 1999 |
The p-norm generalization of the LMS algorithm for adaptive filtering J Kivinen, MK Warmuth, B Hassibi IEEE Transactions on Signal Processing 54 (5), 1782-1793, 2006 | 93 | 2006 |
Mixed Bregman clustering with approximation guarantees R Nock, P Luosto, J Kivinen Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008 | 50 | 2008 |
Learning rules with local exceptions J Kivinen, H Mannila, E Ukkonen INSTITUTE OF MATHEMATICS AND ITS APPLICATIONS CONFERENCE SERIES 53, 35-35, 1994 | 36 | 1994 |
Using experts for predicting continuous outcomes J Kivinen, MK Warmuth Proceedings of the first European conference on Computational learning …, 1994 | 31 | 1994 |
Learning hierarchical rule sets J Kivinen, H Mannila, E Ukkonen Proceedings of the fifth annual workshop on Computational learning theory, 37-44, 1992 | 25 | 1992 |