| 2005 |
|---|
| 12 | EE | Dirk Ormoneit,
Michael J. Black,
Trevor Hastie,
Hedvig Kjellström:
Representing cyclic human motion using functional analysis.
Image Vision Comput. 23(14): 1264-1276 (2005) |
| 2002 |
|---|
| 11 | | Dirk Ormoneit,
Saunak Sen:
Kernel-Based Reinforcement Learning.
Machine Learning 49(2-3): 161-178 (2002) |
| 2001 |
|---|
| 10 | | Urszula Chajewska,
Daphne Koller,
Dirk Ormoneit:
Learning an Agent's Utility Function by Observing Behavior.
ICML 2001: 35-42 |
| 9 | EE | Eran Segal,
Daphne Koller,
Dirk Ormoneit:
Probabilistic Abstraction Hierarchies.
NIPS 2001: 913-920 |
| 8 | EE | Carlos Guestrin,
Dirk Ormoneit:
Robust Combination of Local Controllers.
UAI 2001: 178-185 |
| 7 | EE | Dirk Ormoneit,
Christiane Lemieux,
David J. Fleet:
Lattice Particle Filters.
UAI 2001: 395-402 |
| 2000 |
|---|
| 6 | | Dirk Ormoneit,
Peter W. Glynn:
Kernel-Based Reinforcement Learning in Average-Cost Problems: An Application to Optimal Portfolio Choice.
NIPS 2000: 1068-1074 |
| 5 | | Dirk Ormoneit,
Hedvig Sidenbladh,
Michael J. Black,
Trevor Hastie:
Learning and Tracking Cyclic Human Motion.
NIPS 2000: 894-900 |
| 1999 |
|---|
| 4 | EE | Dirk Ormoneit,
Trevor Hastie:
Optimal Kernel Shapes for Local Linear Regression.
NIPS 1999: 540-546 |
| 3 | EE | Dirk Ormoneit:
A regularization approach to continuous learning with an application to financial derivatives pricing.
Neural Networks 12(10): 1405-1412 (1999) |
| 1998 |
|---|
| 2 | EE | Dirk Ormoneit,
Volker Tresp:
Averaging, maximum penalized likelihood and Bayesian estimation for improving Gaussian mixture probability density estimates.
IEEE Transactions on Neural Networks 9(4): 639-650 (1998) |
| 1995 |
|---|
| 1 | EE | Dirk Ormoneit,
Volker Tresp:
Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging.
NIPS 1995: 542-548 |
