Jyrki Kivinen

40 papers A* 8A 1B 6Journal 11Unranked 12
YearRankTypeTitle / Venue / Authors
2016 — ch.
Attribute-Efficient Learning.
Encyclopedia of Algorithms
Jyrki Kivinen
2014 J jnl
Guest Editors' introduction.
Theor. Comput. Sci.
Jyrki Kivinen, Csaba Szepesvári, Thomas Zeugmann
2011 B ed.
Algorithmic Learning Theory - 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011. Proceedings
ALT
Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann
2011 B conf
Editors' Introduction.
ALT
Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann
2010 B conf
Gaussian Clusters and Noise: An Approach Based on the Minimum Description Length Principle.
Discovery Science
Panu Luosto, Jyrki Kivinen, Heikki Mannila
2010 A* conf
Hedging Structured Concepts.
COLT
Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen
2008 — ch.
Attribute-Efficient Learning.
Encyclopedia of Algorithms
Jyrki Kivinen
2008 — conf
Mixed Bregman Clustering with Approximation Guarantees.
ECML/PKDD (2)
Richard Nock, Panu Luosto, Jyrki Kivinen
2006 J jnl
The p-norm generalization of the LMS algorithm for adaptive filtering.
IEEE Trans. Signal Process.
Jyrki Kivinen, Manfred K. Warmuth, Babak Hassibi
2004 J jnl
Online learning with kernels.
IEEE Trans. Signal Process.
Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson
2003 — conf
Channel equalization and the Bayes point machine.
ICASSP (4)
Edward Harrington, Jyrki Kivinen, Robert C. Williamson
2003 B conf
Online Bayes Point Machines.
PAKDD
Edward Harrington, Ralf Herbrich, Jyrki Kivinen, John C. Platt, Robert C. Williamson
2002 A* ed.
Computational Learning Theory, 15th Annual Conference on Computational Learning Theory, COLT 2002, Sydney, Australia, July 8-10, 2002, Proceedings
COLT
Jyrki Kivinen, Robert H. Sloan
2002 J jnl
Guest Editor's Introduction.
Mach. Learn.
Jyrki Kivinen
2002 B conf
Large Margin Classification for Moving Targets.
ALT
Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson
2002 — conf
Online Learning of Linear Classifiers.
Machine Learning Summer School
Jyrki Kivinen
2001 — conf
Online Learning with Kernels.
NIPS
Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson
2001 J jnl
Relative Loss Bounds for Multidimensional Regression Problems.
Mach. Learn.
Jyrki Kivinen, Manfred K. Warmuth
1999 — conf
Averaging Expert Predictions
EuroCOLT
Jyrki Kivinen, Manfred K. Warmuth
1999 A* conf
Boosting as Entropy Projection.
COLT
Jyrki Kivinen, Manfred K. Warmuth
1999 J jnl
Relative loss bounds for single neurons.
IEEE Trans. Neural Networks
David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth
1998 J jnl
Sequential Prediction of Individual Sequences Under General Loss Functions.
IEEE Trans. Inf. Theory
David Haussler, Jyrki Kivinen, Manfred K. Warmuth
1997 J jnl
Exponentiated Gradient Versus Gradient Descent for Linear Predictors.
Inf. Comput.
Jyrki Kivinen, Manfred K. Warmuth
1997 — conf
Relative Loss Bounds for Multidimensional Regression Problems.
NIPS
Jyrki Kivinen, Manfred K. Warmuth
1997 J jnl
The Perceptron Algorithm Versus Winnow: Linear Versus Logarithmic Mistake Bounds when Few Input Variables are Relevant (Technical Note).
Artif. Intell.
Jyrki Kivinen, Manfred K. Warmuth, Peter Auer
1995 A* conf
Additive versus exponentiated gradient updates for linear prediction.
STOC
Jyrki Kivinen, Manfred K. Warmuth
1995 J jnl
Approximate Inference of Functional Dependencies from Relations.
Theor. Comput. Sci.
Jyrki Kivinen, Heikki Mannila
1995 J jnl
Learning Reliably and with One-Sided Error.
Math. Syst. Theory
Jyrki Kivinen
1995 A* conf
The Perceptron Algorithm vs. Winnow: Linear vs. Logarithmic Mistake Bounds when few Input Variables are Relevant.
COLT
Jyrki Kivinen, Manfred K. Warmuth
1995 — conf
Tight worst-case loss bounds for predicting with expert advice.
EuroCOLT
David Haussler, Jyrki Kivinen, Manfred K. Warmuth
1995 — conf
Worst-case Loss Bounds for Single Neurons.
NIPS
David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth
1994 — conf
An ALgorithm for Learning Hierarchical Classifiers.
ECML
Jyrki Kivinen, Heikki Mannila, Esko Ukkonen, Jaak Vilo
1994 A* conf
The Power of Sampling in Knowledge Discovery.
PODS
Jyrki Kivinen, Heikki Mannila
1993 — conf
Learning rules with local exceptions.
EuroCOLT
Jyrki Kivinen, Heikki Mannila, Esko Ukkonen
1993 — conf
Using experts for predicting continuous outcomes.
EuroCOLT
Jyrki Kivinen, Manfred K. Warmuth
1992 A conf
Approximate Dependency Inference from Relations.
ICDT
Jyrki Kivinen, Heikki Mannila
1992 A* conf
Learning Hierarchical Rule Sets.
COLT
Jyrki Kivinen, Heikki Mannila, Esko Ukkonen
1990 — conf
On inducing topologically minimal decision trees.
TAI
Tapio Elomaa, Jyrki Kivinen
1990 B conf
Reliable and Useful Learning with Uniform Probability Distributions.
ALT
Jyrki Kivinen
1989 A* conf
Reliable and Useful Learning.
COLT
Jyrki Kivinen