2008 |
29 | EE | Richard Nock,
Panu Luosto,
Jyrki Kivinen:
Mixed Bregman Clustering with Approximation Guarantees.
ECML/PKDD (2) 2008: 154-169 |
28 | EE | Jyrki Kivinen:
Attribute-Efficient Learning.
Encyclopedia of Algorithms 2008 |
2006 |
27 | EE | Jyrki Kivinen,
Manfred K. Warmuth,
Babak Hassibi:
The p-norm generalization of the LMS algorithm for adaptive filtering.
IEEE Transactions on Signal Processing 54(5): 1782-1793 (2006) |
2003 |
26 | EE | Edward Harrington,
Ralf Herbrich,
Jyrki Kivinen,
John C. Platt,
Robert C. Williamson:
Online Bayes Point Machines.
PAKDD 2003: 241-252 |
2002 |
25 | | Jyrki Kivinen,
Robert H. Sloan:
Computational Learning Theory, 15th Annual Conference on Computational Learning Theory, COLT 2002, Sydney, Australia, July 8-10, 2002, Proceedings
Springer 2002 |
24 | EE | Jyrki Kivinen,
Alex J. Smola,
Robert C. Williamson:
Large Margin Classification for Moving Targets.
ALT 2002: 113-127 |
23 | EE | Jyrki Kivinen:
Online Learning of Linear Classifiers.
Machine Learning Summer School 2002: 235-258 |
22 | | Jyrki Kivinen:
Guest Editor's Introduction.
Machine Learning 47(2-3): 131-132 (2002) |
2001 |
21 | EE | Jyrki Kivinen,
Alex J. Smola,
Robert C. Williamson:
Online Learning with Kernels.
NIPS 2001: 785-792 |
20 | | Jyrki Kivinen,
Manfred K. Warmuth:
Relative Loss Bounds for Multidimensional Regression Problems.
Machine Learning 45(3): 301-329 (2001) |
1999 |
19 | EE | Jyrki Kivinen,
Manfred K. Warmuth:
Boosting as Entropy Projection.
COLT 1999: 134-144 |
18 | EE | Jyrki Kivinen,
Manfred K. Warmuth:
Averaging Expert Predictions
EuroCOLT 1999: 153-167 |
17 | EE | David P. Helmbold,
Jyrki Kivinen,
Manfred K. Warmuth:
Relative loss bounds for single neurons.
IEEE Transactions on Neural Networks 10(6): 1291-1304 (1999) |
1998 |
16 | | David Haussler,
Jyrki Kivinen,
Manfred K. Warmuth:
Sequential Prediction of Individual Sequences Under General Loss Functions.
IEEE Transactions on Information Theory 44(5): 1906-1925 (1998) |
1997 |
15 | | Jyrki Kivinen,
Manfred K. Warmuth:
Relative Loss Bounds for Multidimensional Regression Problems.
NIPS 1997 |
14 | EE | 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) |
13 | | Jyrki Kivinen,
Manfred K. Warmuth:
Exponentiated Gradient Versus Gradient Descent for Linear Predictors.
Inf. Comput. 132(1): 1-63 (1997) |
1995 |
12 | EE | 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 |
11 | | David Haussler,
Jyrki Kivinen,
Manfred K. Warmuth:
Tight worst-case loss bounds for predicting with expert advice.
EuroCOLT 1995: 69-83 |
10 | EE | David P. Helmbold,
Jyrki Kivinen,
Manfred K. Warmuth:
Worst-case Loss Bounds for Single Neurons.
NIPS 1995: 309-315 |
9 | EE | Jyrki Kivinen,
Manfred K. Warmuth:
Additive versus exponentiated gradient updates for linear prediction.
STOC 1995: 209-218 |
8 | | Jyrki Kivinen:
Learning Reliably and with One-Sided Error.
Mathematical Systems Theory 28(2): 141-172 (1995) |
7 | EE | Jyrki Kivinen,
Heikki Mannila:
Approximate Inference of Functional Dependencies from Relations.
Theor. Comput. Sci. 149(1): 129-149 (1995) |
1994 |
6 | | Jyrki Kivinen,
Heikki Mannila,
Esko Ukkonen,
Jaak Vilo:
An ALgorithm for Learning Hierarchical Classifiers.
ECML 1994: 375-378 |
5 | EE | Jyrki Kivinen,
Heikki Mannila:
The Power of Sampling in Knowledge Discovery.
PODS 1994: 77-85 |
1992 |
4 | EE | Jyrki Kivinen,
Heikki Mannila,
Esko Ukkonen:
Learning Hierarchical Rule Sets.
COLT 1992: 37-44 |
3 | EE | Jyrki Kivinen,
Heikki Mannila:
Approximate Dependency Inference from Relations.
ICDT 1992: 86-98 |
1990 |
2 | | Jyrki Kivinen:
Reliable and Useful Learning with Uniform Probability Distributions.
ALT 1990: 209-222 |
1989 |
1 | EE | Jyrki Kivinen:
Reliable and Useful Learning.
COLT 1989: 365-380 |