Jyrki Kivinen

发表

Exponentiated Gradient Versus Gradient Descent for Linear Predictors

Manfred K. Warmuth, Jyrki Kivinen, Jyrki Kivinen, 1997, Inf. Comput..

Additive versus exponentiated gradient updates for linear prediction

Manfred K. Warmuth, Jyrki Kivinen, Jyrki Kivinen, 1995, STOC '95.

Tight worst-case loss bounds for predicting with expert advice

David Haussler, Manfred K. Warmuth, Jyrki Kivinen, 1994, EuroCOLT.

Relative Loss Bounds for Multidimensional Regression Problems

Manfred K. Warmuth, Jyrki Kivinen, Jyrki Kivinen, 1997, Machine Learning.

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

Manfred K. Warmuth, P. Auer, Jyrki Kivinen, 1997, Artif. Intell..

The perceptron algorithm vs. Winnow: linear vs. logarithmic mistake bounds when few input variables are relevant

Manfred K. Warmuth, Jyrki Kivinen, Jyrki Kivinen, 1995, COLT '95.

Relative loss bounds for single neurons

Manfred K. Warmuth, David P. Helmbold, Jyrki Kivinen, 1999, IEEE Trans. Neural Networks.

Averaging Expert Predictions

Manfred K. Warmuth, Jyrki Kivinen, Jyrki Kivinen, 1999, EuroCOLT.

Worst-case Loss Bounds for Single Neurons

Manfred K. Warmuth, David P. Helmbold, Jyrki Kivinen, 1995, NIPS.

Sequential Prediction of Individual Sequences Under General Loss Functions

David Haussler, Manfred K. Warmuth, Jyrki Kivinen, 1998, IEEE Trans. Inf. Theory.

Online learning with kernels

Alexander J. Smola, Robert C. Williamson, Jyrki Kivinen, 2001, IEEE Transactions on Signal Processing.

Online Bayes Point Machines

John C. Platt, Ralf Herbrich, Robert C. Williamson, 2003, PAKDD.

Boosting as entropy projection

Manfred K. Warmuth, Jyrki Kivinen, Jyrki Kivinen, 1999, COLT '99.

The { dollar } p { dollar }-Norm Generalization of the LMS Algorithm for Adaptive Filtering

Manfred K. Warmuth, Jyrki Kivinen, B. Hassibi, 2022 .

Editors' Introduction

Thomas Zeugmann, Csaba Szepesvári, Esko Ukkonen, 2011, ALT.

Online Bayes Point Machines

John C. Platt, R. C. Williamson, Jyrki Kivinen, 2003, PAKDD.

Using experts for predicting continuous outcomes

Manfred K. Warmuth, Jyrki Kivinen, Jyrki Kivinen, 1994, European Conference on Computational Learning Theory.

Guest Editors' introduction

Thomas Zeugmann, Csaba Szepesvári, Jyrki Kivinen, 2014, Theor. Comput. Sci..

The Power of Sampling in Knowledge Discovery the Power of Sampling in Knowledge Discovery

Jyrki Kivinen, H. Mannila, 1993 .

Proceedings of the 15th Annual Conference on Computational Learning Theory

Robert H. Sloan, Jyrki Kivinen, Jyrki Kivinen, 2002 .

Hedging Structured Concepts

Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen, 2010, COLT.

Approximate Inference of Functional Dependencies from Relations

Heikki Mannila, Jyrki Kivinen, Jyrki Kivinen, 1995, Theor. Comput. Sci..

Approximate Dependency Inference from Relations

Heikki Mannila, Jyrki Kivinen, Jyrki Kivinen, 1992, ICDT.

Learning reliably and with one-sided error

Jyrki Kivinen, Jyrki Kivinen, 1995, Mathematical systems theory.

Reliable and useful learning

Jyrki Kivinen, Jyrki Kivinen, 1989, COLT '89.

The power of sampling in knowledge discovery

Heikki Mannila, Jyrki Kivinen, Jyrki Kivinen, 1994, PODS '94.

Gaussian Clusters and Noise: An Approach Based on the Minimum Description Length Principle

Heikki Mannila, Panu Luosto, Jyrki Kivinen, 2010, Discovery Science.

The p-norm generalization of the LMS algorithm for adaptive filtering

Babak Hassibi, Manfred K. Warmuth, Jyrki Kivinen, 2003, IEEE Transactions on Signal Processing.

Online Learning of Linear Classifiers

Jyrki Kivinen, Jyrki Kivinen, 2002, Machine Learning Summer School.

Large Margin Classification for Moving Targets

Alexander J. Smola, Robert C. Williamson, Jyrki Kivinen, 2002, ALT.

Hedging Structured Concepts

Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen, 2010, COLT 2010.

Hedging Structured Concepts

Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen, 2010, COLT 2010.

Online learning with kernels

R. C. Williamson, Jyrki Kivinen, Alex Smola, 2001, IEEE Transactions on Signal Processing.

Learning Small Trees and Graphs That Generalize Learning Small Trees and Graphs That Generalize Contact Information Learning Small Trees and Graphs That Generalize

Jyrki Kivinen, Ari Rantanen, V. Mäkinen, 2022 .