| 2008 |
|---|
| 71 | EE | Achim Rettinger,
Matthias Nickles,
Volker Tresp:
A statistical relational model for trust learning.
AAMAS (2) 2008: 763-770 |
| 70 | EE | Dieter Fensel,
Frank van Harmelen,
Bo Andersson,
Paul Brennan,
Hamish Cunningham,
Emanuele Della Valle,
Florian Fischer,
Zhisheng Huang,
Atanas Kiryakov,
Tony Kyung-il Lee,
Lael Schooler,
Volker Tresp,
Stefan Wesner,
Michael Witbrock,
Ning Zhong:
Towards LarKC: A Platform for Web-Scale Reasoning.
ICSC 2008: 524-529 |
| 69 | EE | Volker Tresp,
Markus Bundschus,
Achim Rettinger,
Yi Huang:
Towards Machine Learning on the Semantic Web.
URSW (LNCS Vol.) 2008: 282-314 |
| 2007 |
|---|
| 68 | EE | Achim Rettinger,
Matthias Nickles,
Volker Tresp:
Learning Initial Trust Among Interacting Agents.
CIA 2007: 313-327 |
| 67 | EE | Anton Schwaighofer,
Mathäus Dejori,
Volker Tresp,
Martin Stetter:
Structure Learning with Nonparametric Decomposable Models.
ICANN (1) 2007: 119-128 |
| 66 | EE | Shipeng Yu,
Volker Tresp,
Kai Yu:
Robust multi-task learning with t-processes.
ICML 2007: 1103-1110 |
| 65 | EE | Zhao Xu,
Volker Tresp,
Shipeng Yu,
Kai Yu,
Hans-Peter Kriegel:
Fast Inference in Infinite Hidden Relational Models.
MLG 2007 |
| 64 | EE | Ruxandra Lupas Scheiterer,
Dragan Obradovic,
Volker Tresp:
Tailored-to-Fit Bayesian Network Modeling of Expert Diagnostic Knowledge.
VLSI Signal Processing 49(2): 301-316 (2007) |
| 2006 |
|---|
| 63 | EE | Shipeng Yu,
Kai Yu,
Volker Tresp,
Hans-Peter Kriegel:
Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures.
ECML 2006: 841-848 |
| 62 | EE | Kai Yu,
Jinbo Bi,
Volker Tresp:
Active learning via transductive experimental design.
ICML 2006: 1081-1088 |
| 61 | EE | Shipeng Yu,
Kai Yu,
Volker Tresp,
Hans-Peter Kriegel:
Collaborative ordinal regression.
ICML 2006: 1089-1096 |
| 60 | EE | Shipeng Yu,
Kai Yu,
Volker Tresp,
Hans-Peter Kriegel,
Mingrui Wu:
Supervised probabilistic principal component analysis.
KDD 2006: 464-473 |
| 59 | EE | Kai Yu,
Wei Chu,
Shipeng Yu,
Volker Tresp,
Zhao Xu:
Stochastic Relational Models for Discriminative Link Prediction.
NIPS 2006: 1553-1560 |
| 58 | EE | Zhao Xu,
Volker Tresp,
Kai Yu,
Hans-Peter Kriegel:
Infinite Hidden Relational Models.
UAI 2006 |
| 57 | EE | Shipeng Yu,
Kai Yu,
Volker Tresp,
Hans-Peter Kriegel:
Multi-Output Regularized Feature Projection.
IEEE Trans. Knowl. Data Eng. 18(12): 1600-1613 (2006) |
| 2005 |
|---|
| 56 | EE | Kai Yu,
Shipeng Yu,
Volker Tresp:
Multi-Output Regularized Projection.
CVPR (2) 2005: 597-602 |
| 55 | EE | Yi Huang,
Kai Yu,
Matthias Schubert,
Shipeng Yu,
Volker Tresp,
Hans-Peter Kriegel:
Hierarchy-Regularized Latent Semantic Indexing.
ICDM 2005: 178-185 |
| 54 | EE | Zhao Xu,
Volker Tresp,
Kai Yu,
Shipeng Yu,
Hans-Peter Kriegel:
Dirichlet enhanced relational learning.
ICML 2005: 1004-1011 |
| 53 | EE | Kai Yu,
Volker Tresp,
Anton Schwaighofer:
Learning Gaussian processes from multiple tasks.
ICML 2005: 1012-1019 |
| 52 | EE | Shipeng Yu,
Kai Yu,
Volker Tresp:
Soft Clustering on Graphs.
NIPS 2005 |
| 51 | EE | Shipeng Yu,
Kai Yu,
Volker Tresp,
Hans-Peter Kriegel:
A Probabilistic Clustering-Projection Model for Discrete Data.
PKDD 2005: 417-428 |
| 50 | EE | Kai Yu,
Shipeng Yu,
Volker Tresp:
Multi-label informed latent semantic indexing.
SIGIR 2005: 258-265 |
| 2004 |
|---|
| 49 | EE | Kai Yu,
Volker Tresp:
Heterogenous Data Fusion via a Probabilistic Latent-Variable Model.
ARCS 2004: 20-30 |
| 48 | | Kai Yu,
Shipeng Yu,
Volker Tresp:
Dirichlet Enhanced Latent Semantic Analysis.
LWA 2004: 221-226 |
| 47 | EE | Anton Schwaighofer,
Volker Tresp,
Kai Yu:
Learning Gaussian Process Kernels via Hierarchical Bayes.
NIPS 2004 |
| 46 | EE | Kai Yu,
Volker Tresp,
Shipeng Yu:
A nonparametric hierarchical bayesian framework for information filtering.
SIGIR 2004: 353-360 |
| 45 | EE | Kai Yu,
Anton Schwaighofer,
Volker Tresp,
Xiaowei Xu,
Hans-Peter Kriegel:
Probabilistic Memory-Based Collaborative Filtering.
IEEE Trans. Knowl. Data Eng. 16(1): 56-69 (2004) |
| 44 | EE | Michael Haft,
Reimar Hofmann,
Volker Tresp:
Generative binary codes.
Pattern Anal. Appl. 6(4): 269-284 (2004) |
| 2003 |
|---|
| 43 | EE | Kai Yu,
Wei-Ying Ma,
Volker Tresp,
Zhao Xu,
Xiaofei He,
HongJiang Zhang,
Hans-Peter Kriegel:
Knowing a tree from the forest: art image retrieval using a society of profiles.
ACM Multimedia 2003: 622-631 |
| 42 | EE | Zhao Xu,
Xiaowei Xu,
Kai Yu,
Volker Tresp:
A Hybrid Relevance-Feedback Approach to Text Retrieval.
ECIR 2003: 281-293 |
| 41 | EE | Zhao Xu,
Kai Yu,
Volker Tresp,
Xiaowei Xu,
Jizhi Wang:
Representative Sampling for Text Classification Using Support Vector Machines.
ECIR 2003: 393-407 |
| 40 | EE | Volker Tresp,
Kai Yu:
An Introduction to Nonparametric Hierarchical Bayesian Modelling with a Focus on Multi-agent Learning.
European Summer School on Multi-AgentControl 2003: 290-312 |
| 39 | EE | Anton Schwaighofer,
Marian Grigoras,
Volker Tresp,
Clemens Hoffmann:
GPPS: A Gaussian Process Positioning System for Cellular Networks.
NIPS 2003 |
| 38 | | Kai Yu,
Anton Schwaighofer,
Volker Tresp,
Wei-Ying Ma,
HongJiang Zhang:
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes.
UAI 2003: 616-623 |
| 2002 |
|---|
| 37 | EE | Kai Yu,
Xiaowei Xu,
Anton Schwaighofer,
Volker Tresp,
Hans-Peter Kriegel:
Removing redundancy and inconsistency in memory-based collaborative filtering.
CIKM 2002: 52-59 |
| 36 | EE | Anton Schwaighofer,
Volker Tresp,
Peter Mayer,
Alexander K. Scheel,
Gerhard Müller:
The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging.
NIPS 2002: 1409-1416 |
| 35 | EE | Anton Schwaighofer,
Volker Tresp:
Transductive and Inductive Methods for Approximate Gaussian Process Regression.
NIPS 2002: 953-960 |
| 2001 |
|---|
| 34 | | Todd K. Leen,
Thomas G. Dietterich,
Volker Tresp:
Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA
MIT Press 2001 |
| 33 | EE | Joachim Horn,
Thomas Birkhölzer,
Oliver Hogl,
Marco Pellegrino,
Ruxandra Scheiterer,
Kai-Uwe Schmidt,
Volker Tresp:
Knowledge Acquisition and Automated Generation of Bayesian Networks for a Medical Dialogue and Advisory System.
AIME 2001: 199-202 |
| 32 | EE | Volker Tresp,
Anton Schwaighofer:
Scalable Kernel Systems.
ICANN 2001: 285-291 |
| 31 | EE | Anton Schwaighofer,
Volker Tresp:
The Bayesian Committee Support Vector Machine.
ICANN 2001: 411-420 |
| 30 | | Volker Tresp:
Scaling Kernel-Based Systems to Large Data Sets.
Data Min. Knowl. Discov. 5(3): 197-211 (2001) |
| 2000 |
|---|
| 29 | EE | Volker Tresp:
The generalized Bayesian committee machine.
KDD 2000: 130-139 |
| 28 | | Volker Tresp:
Mixtures of Gaussian Processes.
NIPS 2000: 654-660 |
| 27 | | Volker Tresp:
A Bayesian Committee Machine.
Neural Computation 12(11): 2719-2741 (2000) |
| 1999 |
|---|
| 26 | EE | Thomas Briegel,
Volker Tresp:
Robust Neural Network Regression for Offline and Online Learning.
NIPS 1999: 407-413 |
| 25 | EE | Volker Tresp,
Michael Haft,
Reimar Hofmann:
Mixture Approximations to Bayesian Networks.
UAI 1999: 639-646 |
| 24 | EE | Volker Tresp,
Thomas Briegel,
J. Moody:
Neural-network models for the blood glucose metabolism of a diabetic.
IEEE Transactions on Neural Networks 10(5): 1204-1213 (1999) |
| 1998 |
|---|
| 23 | EE | Thomas Briegel,
Volker Tresp:
Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models.
NIPS 1998: 403-409 |
| 22 | EE | Jaakko Hollmén,
Volker Tresp:
Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model.
NIPS 1998: 889-895 |
| 21 | 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) |
| 20 | | Volker Tresp,
Reimar Hofmann:
Nonlinear Time-Series Prediction with Missing and Noisy Data.
Neural Computation 10(3): 731-747 (1998) |
| 1997 |
|---|
| 19 | | Michiaki Taniguchi,
Volker Tresp:
Combining Regularized Neural Networks.
ICANN 1997: 349-354 |
| 18 | | Volker Tresp,
Thomas Briegel:
A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose Prediction.
NIPS 1997 |
| 17 | | Reimar Hofmann,
Volker Tresp:
Nonlinear Markov Networks for Continuous Variables.
NIPS 1997 |
| 16 | | Volker Tresp,
Jürgen Hollatz,
Subutai Ahmad:
Representing Probabilistic Rules with Networks of Gaussian Basis Functions.
Machine Learning 27(2): 173-200 (1997) |
| 15 | EE | Michiaki Taniguchi,
Volker Tresp:
Averaging Regularized Estimators.
Neural Computation 9(5): 1163-1178 (1997) |
| 1996 |
|---|
| 14 | EE | Volker Tresp,
Ralph Neuneier,
Hans-Georg Zimmermann:
Early Brain Damage.
NIPS 1996: 669-675 |
| 1995 |
|---|
| 13 | EE | Reimar Hofmann,
Volker Tresp:
Discovering Structure in Continuous Variables Using Bayesian Networks.
NIPS 1995: 500-506 |
| 12 | EE | Dirk Ormoneit,
Volker Tresp:
Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging.
NIPS 1995: 542-548 |
| 11 | | Volker Tresp:
Die besonderen Eigenschaften Neuronaler Netze bei der Approximation von Funktionen.
KI 9(5): 12-17 (1995) |
| 1994 |
|---|
| 10 | EE | Volker Tresp,
Michiaki Taniguchi:
Combining Estimators Using Non-Constant Weighting Functions.
NIPS 1994: 419-426 |
| 9 | EE | Volker Tresp,
Ralph Neuneier,
Subutai Ahmad:
Efficient Methods for Dealing with Missing Data in Supervised Learning.
NIPS 1994: 689-696 |
| 1993 |
|---|
| 8 | EE | Volker Tresp,
Subutai Ahmad,
Ralph Neuneier:
Training Neural Networks with Deficient Data.
NIPS 1993: 128-135 |
| 1992 |
|---|
| 7 | | Martin F. Schlang,
Volker Tresp,
Klaus Abraham-Fuchs,
Wolfgang Härer,
P. Weismüller:
Neuronale Netze zur Segmentierung und Clusterung von biomagnetischen Signalen.
DAGM-Symposium 1992: 180-185 |
| 6 | | Jürgen Hollatz,
Volker Tresp:
Integrating Rule-Based Knowledge into Neural Computing.
DAGM-Symposium 1992: 88-95 |
| 5 | EE | Subutai Ahmad,
Volker Tresp:
Some Solutions to the Missing Feature Problem in Vision.
NIPS 1992: 393-400 |
| 4 | EE | Volker Tresp,
Jürgen Hollatz,
Subutai Ahmad:
Network Structuring and Training Using Rule-Based Knowledge.
NIPS 1992: 871-878 |
| 1991 |
|---|
| 3 | | Volker Tresp:
A Neural Architecture for 2D and 3D Vision.
DAGM-Symposium 1991: 437-445 |
| 2 | EE | Martin Röscheisen,
Reimar Hofmann,
Volker Tresp:
Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency.
NIPS 1991: 659-666 |
| 1990 |
|---|
| 1 | EE | Volker Tresp:
A Neural Network Approach for Three-Dimensional Object Recognition.
NIPS 1990: 306-312 |
