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ORCIDJyrki Kivinen
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Journal Articles
- 2014
[j11]Jyrki Kivinen
, Csaba Szepesvári, Thomas Zeugmann:
Guest Editors' introduction. Theor. Comput. Sci. 519: 1-3 (2014)- 2006
- [j10]Jyrki Kivinen, Manfred K. Warmuth, Babak Hassibi:
The p-norm generalization of the LMS algorithm for adaptive filtering. IEEE Trans. Signal Process. 54(5): 1782-1793 (2006) - 2004
- [j9]Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson:
Online learning with kernels. IEEE Trans. Signal Process. 52(8): 2165-2176 (2004) - 2002
- [j8]Jyrki Kivinen:
Guest Editor's Introduction. Mach. Learn. 47(2-3): 131-132 (2002) - 2001
- [j7]Jyrki Kivinen, Manfred K. Warmuth:
Relative Loss Bounds for Multidimensional Regression Problems. Mach. Learn. 45(3): 301-329 (2001) - 1999
- [j6]David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth:
Relative loss bounds for single neurons. IEEE Trans. Neural Networks 10(6): 1291-1304 (1999) - 1998
- [j5]David Haussler, Jyrki Kivinen, Manfred K. Warmuth:
Sequential Prediction of Individual Sequences Under General Loss Functions. IEEE Trans. Inf. Theory 44(5): 1906-1925 (1998) - 1997
- [j4]Jyrki Kivinen, Manfred K. Warmuth, Peter Auer:
The Perceptron Algorithm Versus Winnow: Linear Versus Logarithmic Mistake Bounds when Few Input Variables are Relevant (Technical Note). Artif. Intell. 97(1-2): 325-343 (1997) - [j3]Jyrki Kivinen, Manfred K. Warmuth:
Exponentiated Gradient Versus Gradient Descent for Linear Predictors. Inf. Comput. 132(1): 1-63 (1997) - 1995
- [j2]Jyrki Kivinen:
Learning Reliably and with One-Sided Error. Math. Syst. Theory 28(2): 141-172 (1995) - [j1]Jyrki Kivinen, Heikki Mannila:
Approximate Inference of Functional Dependencies from Relations. Theor. Comput. Sci. 149(1): 129-149 (1995)
Conference and Workshop Papers
- 2011
- [c25]Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann:
Editors' Introduction. ALT 2011: 1-13 - 2010
- [c24]Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen:
Hedging Structured Concepts. COLT 2010: 93-105 - [c23]Panu Luosto, Jyrki Kivinen, Heikki Mannila:
Gaussian Clusters and Noise: An Approach Based on the Minimum Description Length Principle. Discovery Science 2010: 251-265 - 2008
- [c22]Richard Nock, Panu Luosto, Jyrki Kivinen:
Mixed Bregman Clustering with Approximation Guarantees. ECML/PKDD (2) 2008: 154-169 - 2003
- [c21]Edward Harrington, Jyrki Kivinen, Robert C. Williamson:
Channel equalization and the Bayes point machine. ICASSP (4) 2003: 493-496 - [c20]Edward Harrington, Ralf Herbrich, Jyrki Kivinen, John C. Platt, Robert C. Williamson:
Online Bayes Point Machines. PAKDD 2003: 241-252 - 2002
- [c19]Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson:
Large Margin Classification for Moving Targets. ALT 2002: 113-127 - [c18]Jyrki Kivinen:
Online Learning of Linear Classifiers. Machine Learning Summer School 2002: 235-258 - 2001
- [c17]Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson:
Online Learning with Kernels. NIPS 2001: 785-792 - 1999
- [c16]Jyrki Kivinen, Manfred K. Warmuth:
Boosting as Entropy Projection. COLT 1999: 134-144 - [c15]Jyrki Kivinen, Manfred K. Warmuth:
Averaging Expert Predictions. EuroCOLT 1999: 153-167 - 1997
- [c14]Jyrki Kivinen, Manfred K. Warmuth:
Relative Loss Bounds for Multidimensional Regression Problems. NIPS 1997: 287-293 - 1995
- [c13]Jyrki Kivinen, Manfred K. Warmuth:
The Perceptron Algorithm vs. Winnow: Linear vs. Logarithmic Mistake Bounds when few Input Variables are Relevant. COLT 1995: 289-296 - [c12]David Haussler, Jyrki Kivinen, Manfred K. Warmuth:
Tight worst-case loss bounds for predicting with expert advice. EuroCOLT 1995: 69-83 - [c11]David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth:
Worst-case Loss Bounds for Single Neurons. NIPS 1995: 309-315 - [c10]Jyrki Kivinen, Manfred K. Warmuth:
Additive versus exponentiated gradient updates for linear prediction. STOC 1995: 209-218 - 1994
- [c9]Jyrki Kivinen, Heikki Mannila, Esko Ukkonen, Jaak Vilo:
An ALgorithm for Learning Hierarchical Classifiers. ECML 1994: 375-378 - [c8]Jyrki Kivinen, Heikki Mannila:
The Power of Sampling in Knowledge Discovery. PODS 1994: 77-85 - 1993
- [c7]Jyrki Kivinen, Heikki Mannila, Esko Ukkonen:
Learning rules with local exceptions. EuroCOLT 1993: 35-46 - [c6]Jyrki Kivinen, Manfred K. Warmuth:
Using experts for predicting continuous outcomes. EuroCOLT 1993: 109-120 - 1992
- [c5]Jyrki Kivinen, Heikki Mannila, Esko Ukkonen:
Learning Hierarchical Rule Sets. COLT 1992: 37-44 - [c4]Jyrki Kivinen, Heikki Mannila:
Approximate Dependency Inference from Relations. ICDT 1992: 86-98 - 1990
- [c3]Jyrki Kivinen:
Reliable and Useful Learning with Uniform Probability Distributions. ALT 1990: 209-222 - [c2]Tapio Elomaa, Jyrki Kivinen:
On inducing topologically minimal decision trees. TAI 1990: 746-752 - 1989
- [c1]Jyrki Kivinen:
Reliable and Useful Learning. COLT 1989: 365-380
Editorship
- 2011
- [e2]Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann:
Algorithmic Learning Theory - 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011. Proceedings. Lecture Notes in Computer Science 6925, Springer 2011, ISBN 978-3-642-24411-7 [contents] - 2002
- [e1]Jyrki Kivinen, Robert H. Sloan:
Computational Learning Theory, 15th Annual Conference on Computational Learning Theory, COLT 2002, Sydney, Australia, July 8-10, 2002, Proceedings. Lecture Notes in Computer Science 2375, Springer 2002, ISBN 3-540-43836-X [contents]
Reference Works
- 2016
- [r2]Jyrki Kivinen:
Attribute-Efficient Learning. Encyclopedia of Algorithms 2016: 160-162 - 2008
- [r1]Jyrki Kivinen:
Attribute-Efficient Learning. Encyclopedia of Algorithms 2008
Coauthor Index
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