Online learning with kernels J Kivinen, AJ Smola, RC Williamson Signal Processing, IEEE Transactions on 52 (8), 2165-2176, 2004 | 1387 | 2004 |
Online learning with kernels J Kivinen, AJ Smola, RC Williamson Advances in neural information processing systems 1, 785-792, 2002 | 1387 | 2002 |
Exponentiated gradient versus gradient descent for linear predictors J Kivinen, MK Warmuth information and computation 132 (1), 1-63, 1997 | 1230* | 1997 |
Approximate inference of functional dependencies from relations J Kivinen, H Mannila Theoretical Computer Science 149 (1), 129-149, 1995 | 308 | 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 | 215 | 1998 |
Relative loss bounds for multidimensional regression problems J Kivinen, MKK Warmuth Advances in neural information processing systems 10, 1997 | 196 | 1997 |
The perceptron algorithm vs. winnow: linear vs. logarithmic mistake bounds when few input variables are relevant J Kivinen, MK Warmuth Proceedings of the eighth annual conference on Computational learning theory …, 1995 | 191 | 1995 |
Averaging expert predictions J Kivinen, MK Warmuth European Conference on Computational Learning Theory, 153-167, 1999 | 186 | 1999 |
The power of sampling in knowledge discovery J Kivinen, H Mannila Proceedings of the thirteenth ACM SIGACT-SIGMOD-SIGART symposium on …, 1994 | 182 | 1994 |
Boosting as entropy projection J Kivinen, MK Warmuth Proceedings of the twelfth annual conference on Computational learning …, 1999 | 162 | 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 | 149 | 1995 |
Hedging Structured Concepts. WM Koolen, MK Warmuth, J Kivinen COLT, 93-105, 2010 | 133 | 2010 |
Approximate dependency inference from relations J Kivinen, H Mannila International Conference on Database Theory, 86-98, 1992 | 131 | 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 | 128 | 1995 |
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 | 110 | 2006 |
Relative loss bounds for single neurons DP Helmbold, J Kivinen, MK Warmuth Neural Networks, IEEE Transactions on 10 (6), 1291-1304, 1999 | 109* | 1999 |
Mixed Bregman clustering with approximation guarantees R Nock, P Luosto, J Kivinen Joint european conference on machine learning and knowledge discovery in …, 2008 | 51 | 2008 |
Learning rules with local exceptions J Kivinen, H Mannila, E Ukkonen European Conference on Computational Learning Theory, 35-46, 1994 | 38 | 1994 |
Using experts for predicting continuous outcomes J Kivinen, M Warmuth Levine's Working Paper Archive, 2010 | 36 | 2010 |
Online bayes point machines E Harrington, R Herbrich, J Kivinen, J Platt, RC Williamson Advances in Knowledge Discovery and Data Mining: 7th Pacific-Asia Conference …, 2003 | 25 | 2003 |