2009 |
34 | EE | David H. Stern,
Ralf Herbrich,
Thore Graepel:
Matchbox: large scale online bayesian recommendations.
WWW 2009: 111-120 |
2008 |
33 | EE | Thore Graepel,
Ralf Herbrich:
Large scale data analysis and modelling in online services and advertising.
KDD 2008: 2 |
2007 |
32 | EE | David H. Stern,
Ralf Herbrich,
Thore Graepel:
Learning to solve game trees.
ICML 2007: 839-846 |
31 | EE | Pierre Dangauthier,
Ralf Herbrich,
Tom Minka,
Thore Graepel:
TrueSkill Through Time: Revisiting the History of Chess.
NIPS 2007 |
2006 |
30 | EE | David H. Stern,
Ralf Herbrich,
Thore Graepel:
Bayesian pattern ranking for move prediction in the game of Go.
ICML 2006: 873-880 |
29 | EE | Ralf Herbrich,
Tom Minka,
Thore Graepel:
TrueSkillTM: A Bayesian Skill Rating System.
NIPS 2006: 569-576 |
2005 |
28 | EE | Arthur Gretton,
Ralf Herbrich,
Alexander J. Smola,
Olivier Bousquet,
Bernhard Schölkopf:
Kernel Methods for Measuring Independence.
Journal of Machine Learning Research 6: 2075-2129 (2005) |
27 | EE | Shivani Agarwal,
Thore Graepel,
Ralf Herbrich,
Sariel Har-Peled,
Dan Roth:
Generalization Bounds for the Area Under the ROC Curve.
Journal of Machine Learning Research 6: 393-425 (2005) |
26 | EE | Thore Graepel,
Ralf Herbrich,
John Shawe-Taylor:
PAC-Bayesian Compression Bounds on the Prediction Error of Learning Algorithms for Classification.
Machine Learning 59(1-2): 55-76 (2005) |
2004 |
25 | EE | Shivani Agarwal,
Thore Graepel,
Ralf Herbrich,
Dan Roth:
A Large Deviation Bound for the Area Under the ROC Curve.
NIPS 2004 |
2003 |
24 | EE | Thore Graepel,
Ralf Herbrich:
Invariant Pattern Recognition by Semi-Definite Programming Machines.
NIPS 2003 |
23 | EE | Thore Graepel,
Ralf Herbrich,
Andriy Kharechko,
John Shawe-Taylor:
Semi-Definite Programming by Perceptron Learning.
NIPS 2003 |
22 | EE | Edward Harrington,
Ralf Herbrich,
Jyrki Kivinen,
John C. Platt,
Robert C. Williamson:
Online Bayes Point Machines.
PAKDD 2003: 241-252 |
21 | EE | Ralf Herbrich,
Thore Graepel:
Introduction to the Special Issue on Learning Theory.
Journal of Machine Learning Research 4: 755-757 (2003) |
2002 |
20 | | Yaoyong Li,
Hugo Zaragoza,
Ralf Herbrich,
John Shawe-Taylor,
Jaz S. Kandola:
The Perceptron Algorithm with Uneven Margins.
ICML 2002: 379-386 |
19 | EE | Neil D. Lawrence,
Matthias Seeger,
Ralf Herbrich:
Fast Sparse Gaussian Process Methods: The Informative Vector Machine.
NIPS 2002: 609-616 |
18 | EE | Stephen E. Robertson,
Steve Walker,
Hugo Zaragoza,
Ralf Herbrich:
Microsoft Cambridge at TREC 2002: Filtering Track.
TREC 2002 |
17 | | Ralf Herbrich,
Thore Graepel:
A PAC-Bayesian margin bound for linear classifiers.
IEEE Transactions on Information Theory 48(12): 3140-3150 (2002) |
16 | EE | Ralf Herbrich,
Robert C. Williamson:
Algorithmic Luckiness.
Journal of Machine Learning Research 3: 175-212 (2002) |
2001 |
15 | EE | Bernhard Schölkopf,
Ralf Herbrich,
Alex J. Smola:
A Generalized Representer Theorem.
COLT/EuroCOLT 2001: 416-426 |
14 | EE | Thore Graepel,
Mike Goutrié,
Marco Krüger,
Ralf Herbrich:
Learning on Graphs in the Game of Go.
ICANN 2001: 347-352 |
13 | EE | Ralf Herbrich,
Robert C. Williamson:
Algorithmic Luckiness.
NIPS 2001: 391-397 |
12 | EE | Ralf Herbrich,
Thore Graepel,
Colin Campbell:
Bayes Point Machines.
Journal of Machine Learning Research 1: 245-279 (2001) |
2000 |
11 | | Thore Graepel,
Ralf Herbrich,
John Shawe-Taylor:
Generalisation Error Bounds for Sparse Linear Classifiers.
COLT 2000: 298-303 |
10 | | Ralf Herbrich,
Thore Graepel,
John Shawe-Taylor:
Sparsity vs. Large Margins for Linear Classifiers.
COLT 2000: 304-308 |
9 | EE | Ralf Herbrich,
Thore Graepel,
Colin Campbell:
Robust Bayes Point Machines.
ESANN 2000: 49-54 |
8 | | Thore Graepel,
Ralf Herbrich,
Robert C. Williamson:
From Margin to Sparsity.
NIPS 2000: 210-216 |
7 | | Ralf Herbrich,
Thore Graepel:
A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work.
NIPS 2000: 224-230 |
6 | | Thore Graepel,
Ralf Herbrich:
The Kernel Gibbs Sampler.
NIPS 2000: 514-520 |
5 | | Ralf Herbrich,
Thore Graepel:
Large Scale Bayes Point Machines.
NIPS 2000: 528-534 |
1999 |
4 | EE | Thore Graepel,
Ralf Herbrich,
Klaus Obermayer:
Bayesian Transduction.
NIPS 1999: 456-462 |
1998 |
3 | EE | Thore Graepel,
Ralf Herbrich,
Peter Bollmann-Sdorra,
Klaus Obermayer:
Classification on Pairwise Proximity Data.
NIPS 1998: 438-444 |
1997 |
2 | | Tobias Scheffer,
Ralf Herbrich:
Unbiased Assesment of Learning Algorithms.
IJCAI (2) 1997: 798-803 |
1996 |
1 | | Tobias Scheffer,
Ralf Herbrich,
Fritz Wysotzki:
Efficient Theta-Subsumption Based on Graph Algorithms.
Inductive Logic Programming Workshop 1996: 212-228 |