Jyrki Kivinen

According to our database1, Jyrki Kivinen authored at least 34 papers between 1989 and 2016.

Collaborative distances:



In proceedings 
PhD thesis 


On csauthors.net:


Attribute-Efficient Learning.
Encyclopedia of Algorithms, 2016

Guest Editors' introduction.
Theor. Comput. Sci., 2014

Editors' Introduction.
Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

Gaussian Clusters and Noise: An Approach Based on the Minimum Description Length Principle.
Proceedings of the Discovery Science - 13th International Conference, 2010

Hedging Structured Concepts.
Proceedings of the COLT 2010, 2010

Attribute-Efficient Learning.
Proceedings of the Encyclopedia of Algorithms - 2008 Edition, 2008

Mixed Bregman Clustering with Approximation Guarantees.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

The p-norm generalization of the LMS algorithm for adaptive filtering.
IEEE Trans. Signal Process., 2006

Online learning with kernels.
IEEE Trans. Signal Process., 2004

Online Bayes Point Machines.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2003

Channel equalization and the Bayes point machine.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Guest Editor's Introduction.
Mach. Learn., 2002

Online Learning of Linear Classifiers.
Proceedings of the Advanced Lectures on Machine Learning, 2002

Large Margin Classification for Moving Targets.
Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

Relative Loss Bounds for Multidimensional Regression Problems.
Mach. Learn., 2001

Relative loss bounds for single neurons.
IEEE Trans. Neural Networks, 1999

Averaging Expert Predictions
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

Boosting as Entropy Projection.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

Sequential Prediction of Individual Sequences Under General Loss Functions.
IEEE Trans. Inf. Theory, 1998

Exponentiated Gradient Versus Gradient Descent for Linear Predictors.
Inf. Comput., 1997

The Perceptron Algorithm Versus Winnow: Linear Versus Logarithmic Mistake Bounds when Few Input Variables are Relevant (Technical Note).
Artif. Intell., 1997

Approximate Inference of Functional Dependencies from Relations.
Theor. Comput. Sci., 1995

Learning Reliably and with One-Sided Error.
Math. Syst. Theory, 1995

Additive versus exponentiated gradient updates for linear prediction.
Proceedings of the Twenty-Seventh Annual ACM Symposium on Theory of Computing, 1995

Worst-case Loss Bounds for Single Neurons.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Tight worst-case loss bounds for predicting with expert advice.
Proceedings of the Computational Learning Theory, Second European Conference, 1995

The Perceptron Algorithm vs. Winnow: Linear vs. Logarithmic Mistake Bounds when few Input Variables are Relevant.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

The Power of Sampling in Knowledge Discovery.
Proceedings of the Thirteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1994

An ALgorithm for Learning Hierarchical Classifiers.
Proceedings of the Machine Learning: ECML-94, 1994

Approximate Dependency Inference from Relations.
Proceedings of the Database Theory, 1992

Learning Hierarchical Rule Sets.
Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

On inducing topologically minimal decision trees.
Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence, 1990

Reliable and Useful Learning with Uniform Probability Distributions.
Proceedings of the Algorithmic Learning Theory, First International Workshop, 1990

Reliable and Useful Learning.
Proceedings of the Second Annual Workshop on Computational Learning Theory, 1989