- Bayesian Belief Networks for Data Mining Harald Steck and Volker Tresp
- Committee Machines Volker Tresp
- Relation Prediction in Multi-Relational Domains using Matrix Factorization
- Fast Inference in Infinite Hidden Relational Models Zhao Xu zhao.xu@web.de
- Towards LarKC: a Platform for Web-scale Reasoning Dieter Fensel (University of Innsbruck) Frank van Harmelen (Vrije Universiteit Amsterdam)
- Small Journal Name, 9, 131 (1992) c 1992 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Structure Learning with Nonparametric Decomposable Models
- 32 1541-1672/10/$26.00 2010 IEEE IEEE INTELLIGENT SYSTEMS Published by the IEEE Computer Society
- Dirichlet Processes and Nonparametric Bayesian Modelling
- Supervised Probabilistic Principal Component Analysis Shipeng Yu1,2
- DOI 10.1007/s10994-010-5211-x Statistical relational learning of trust
- Predictive Modeling using Features derived from Paths in Relational Graphs
- Digging for Knowledge with Information Extraction: A Case Study on Human Gene-Disease Associations
- Volker Tresp Corporate Technology
- The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging
- Volker Tresp Corporate Technology
- A Scalable Kernel Approach to Learning in Semantic Graphs with Applications to Linked Data
- Combined Structured and Keyword-Based Search in Textually Enriched Entity-Relationship Graphs
- Hierarchical Bayesian Models for Collaborative Tagging Systems Markus Bundschus, Shipeng Yu, Volker Tresp, Achim Rettinger, Mathaeus Dejori
- BioMed Central Page 1 of 14
- Robust Multi-Task Learning with t-Processes shipeng.yu@siemens.com
- Infinite Hidden Relational Models Institute for Computer Science
- Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures
- Dirichlet Enhanced Relational Learning Zhao Xu zhao.xu@campus.lmu.de
- Blockwise Supervised Inference on Large Graphs Kai Yu kai.yu@siemens.com
- A Probabilistic Clustering-Projection Model for Discrete Data
- An Introduction to Nonparametric Hierarchical Bayesian Modelling with a Focus on
- A Nonparametric Hierarchical Bayesian Framework for Information Filtering
- at 5/2002 ANWENDUNGSAUFSATZ A Nonlinear State Space Model for the
- ARTHRITIS & RHEUMATISM Vol. 46, No. 5, May 2002, pp 11771184
- Transductive and Inductive Methods for Approximate Gaussian Process Regression
- Local Factorization of Functions Technical Report
- Neural Computation, Vol. 12, pages 2719-2741, 2000 A Bayesian Committee Machine
- The Generalized Bayesian Committee Machine [Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge
- NEURAL NETWORK MODELS FOR THE BLOOD GLUCOSE METABOLISM OF A DIABETIC 1 Neural Network Models for the Blood
- Robust Neural Network Regression for Ofine and Online Learning
- Mixture Approximations to Bayesian Networks (In Laskey, K. B., Prade, H., (Eds.), Uncertainty in Artificial Intelligence, Proceedings of the Fifteenth Conference,
- Call-based Fraud Detection in Mobile Communication Networks using a Hierarchical
- Nonlinear Time-Series Prediction with Missing and Volker Tresp and Reimar Hofmann
- in Advances in Neural Information Processing Systems 10, eds. M. Jordan, M. Kearns, S. Solla, MIT-Press, 1998.
- Appearing in NIPS 2005 workshop "Inductive Transfer: 10 Years Later", Whistler, Canada, December, 2005.
- Towards Machine Learning on the Semantic Volker Tresp (1), Markus Bundschus (2), Achim Rettinger (3)
- The Equivalence between Row and Column Linear Regression
- In: Cowan, J. D., Tesauro, G., and Alspector, J., eds., Advances in Neural Information Processing Systems 6, San Mateo, CA, Morgan
- In: G. Tesauro, D. S. Touretzky and T. K. Leen, eds., "Advances in Neural Information Processing Systems 7", MIT Press, Cambridge MA,
- Soft Clustering on Graphs , Shipeng Yu2
- Averaging Regularized Estimators Michiaki Taniguchi and Volker Tresp
- Stochastic Relational Models for Discriminative Link Prediction
- Integrating Ontological Prior Knowledge into Relational Learning Stefan Reckow reckow@mpipsykl.mpg.de
- Committee Machines Volker Tresp
- Early Brain Damage Volker Tresp, Ralph Neuneier and Hans Georg Zimmermann
- In: "Advances in Neural Information Processing Systems 8," MIT Press, Cambridge MA, 1996.
- Materializing and Querying Learned Knowledge Volker Tresp1
- Model-Independent Mean Field Theory as a Local Method for Approximate Propagation of
- Mixtures of Gaussian Processes Volker Tresp
- Data Mining and Knowledge Discovery, Volume 5, Number 3, 2001 Scaling Kernel-Based Systems to Large Data Sets
- In: C. L. Giles, S. J. Hanson, and J. D. Cowan, eds., Ad-vances in Neural Information Processing Systems 5, San Ma-
- Seminar fur Statistik Ludwig Maximilians Universitat Munchen
- Nonparametric Relational Learning for Social Network Analysis
- Statistical modeling of medical indexing processes for biomedical knowledge information discovery from text
- Active Learning via Transductive Experimental Design Kai Yu kai.yu@siemens.com
- Draft paper, to be published in "OMICS A Journal of Integrative Biology" Mining Functional Modules in Genetic Networks with Decomposable
- Multi-Label Informed Latent Semantic Indexing , Shipeng Yu
- FRAUD DETECTION IN COMMUNICATIONS NETWORKS USING NEURAL AND PROBABILISTIC METHODS
- Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
- Multi-Output Regularized Projection Kai Yu Shipeng Yu Volker Tresp
- Representative Sampling for Text Classification using Support Vector Machines
- In: G. Tesauro, D. S. Touretzky and T. K. Leen, eds., "Advances in Neural Information Processing Systems 7", MIT Press, Cambridge MA,
- In: "Advances in Neural Information Processing Systems 10: Proceedings of the 1997 Conference," Michael I. Jordan,
- Multivariate Prediction for Learning in Relational Graphs
- Topic Models for Semantically Annotated Document Collections
- IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 1 Probabilistic Memory-based Collaborative Filtering
- Modeling and Learning Context-Aware Recommendation Scenarios
- Towards BOTTARI: Using Stream Reasoning to Make Sense of Location-Based Micro-Posts
- Integrating Machine Learning in a Semantic Web Platform for Traffic Forecasting and Routing
- Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics
- GRAPHICAL MODELS FOR RELATIONS Modeling Relational Context
- SemanticsinLocation-BasedServices 2 Published by the IEEE Computer Society 1089-7801/11/$26.00 2011 IEEE IEEE INTERNET COMPUTING
- Making Sense of Location-based Micro-posts Using Stream Reasoning
- Noname manuscript No. (will be inserted by the editor)
- A Novel Metric for Information Retrieval in Semantic Networks
