Volker Tresp

Volker Tresp, Michael Haft, Reimar Hofmann: Mixture Approximations to Bayesian Networks. CoRR abs/1301.6744 (2013)

Achim Rettinger, Uta Lösch, Volker Tresp, Claudia d'Amato, Nicola Fanizzi: Mining the Semantic Web - Statistical learning for next generation knowledge bases. Data Min. Knowl. Discov. 24(3): 613-662 (2012)

Achim Rettinger, Hendrik Wermser, Yi Huang, Volker Tresp: Context-aware tensor decomposition for relation prediction in social networks. Social Netw. Analys. Mining 2(4): 373-385 (2012)

Marco Balduini, Irene Celino, Daniele Dell'Aglio, Emanuele Della Valle, Yi Huang, Tony Kyung-il Lee, Seon-Ho Kim, Volker Tresp: BOTTARI: An augmented reality mobile application to deliver personalized and location-based recommendations by continuous analysis of social media streams. J. Web Sem. 16: 33-41 (2012)

Mohamed Yahya, Klaus Berberich, Shady Elbassuoni, Maya Ramanath, Volker Tresp, Gerhard Weikum: Natural Language Questions for the Web of Data. EMNLP-CoNLL 2012: 379-390

Xueyan Jiang, Yi Huang, Maximilian Nickel, Volker Tresp: Combining Information Extraction, Deductive Reasoning and Machine Learning for Relation Prediction. ESWC 2012: 164-178

Xueyan Jiang, Volker Tresp, Yi Huang, Maximilian Nickel, Hans-Peter Kriegel: Scalable Relation Prediction Exploiting Both Intrarelational Correlation and Contextual Information. ECML/PKDD (1) 2012: 601-616

Xueyan Jiang, Volker Tresp, Yi Huang, Maximilian Nickel: Link Prediction in Multi-relational Graphs using Additive Models. SeRSy 2012: 1-12

Maximilian Nickel, Volker Tresp, Hans-Peter Kriegel: Factorizing YAGO: scalable machine learning for linked data. WWW 2012: 271-280

Mohamed Yahya, Klaus Berberich, Shady Elbassuoni, Maya Ramanath, Volker Tresp, Gerhard Weikum: Deep answers for naturally asked questions on the web of data. WWW (Companion Volume) 2012: 445-449

Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang: Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes. CoRR abs/1212.2508 (2012)

Emanuele Della Valle, Irene Celino, Daniele Dell'Aglio, Ralph Grothmann, Florian Steinke, Volker Tresp: Semantic Traffic-Aware Routing Using the LarKC Platform. IEEE Internet Computing 15(6): 15-23 (2011)

Achim Rettinger, Matthias Nickles, Volker Tresp: Statistical relational learning of trust. Machine Learning 82(2): 191-209 (2011)

Hendrik Wermser, Achim Rettinger, Volker Tresp: Modeling and Learning Context-Aware Recommendation Scenarios Using Tensor Decomposition. ASONAM 2011: 137-144

Joshua L. Moore, Florian Steinke, Volker Tresp: A Novel Metric for Information Retrieval in Semantic Networks. ESWC Workshops 2011: 65-79

Irene Celino, Daniele Dell'Aglio, Emanuele Della Valle, Yi Huang, Tony Kyung-il Lee, Seon-Ho Kim, Volker Tresp: Towards BOTTARI: Using Stream Reasoning to Make Sense of Location-Based Micro-posts. ESWC Workshops 2011: 80-87

Volker Tresp, Yi Huang, Xueyan Jiang, Achim Rettinger: Graphical Models for Relations - Modeling Relational Context. KDIR 2011: 114-120

Maximilian Nickel, Volker Tresp, Hans-Peter Kriegel: A Three-Way Model for Collective Learning on Multi-Relational Data. ICML 2011: 809-816

Davide Francesco Barbieri, Daniele Braga, Stefano Ceri, Emanuele Della Valle, Yi Huang, Volker Tresp, Achim Rettinger, Hendrik Wermser: Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics. IEEE Intelligent Systems 25(6): 32-41 (2010)

Markus Bundschus, Anna Bauer-Mehren, Volker Tresp, Laura Inés Furlong, Hans-Peter Kriegel: Digging for knowledge with information extraction: a case study on human gene-disease associations. CIKM 2010: 1845-1848

Yi Huang, Volker Tresp, Markus Bundschus, Achim Rettinger, Hans-Peter Kriegel: Multivariate Prediction for Learning on the Semantic Web. ILP 2010: 92-104

Markus Bundschus, Shipeng Yu, Volker Tresp, Achim Rettinger, Mathäus Dejori, Hans-Peter Kriegel: Hierarchical Bayesian Models for Collaborative Tagging Systems. ICDM 2009: 728-733

Volker Tresp, Kai Yu: Tutorial summary: Learning with dependencies between several response variables. ICML 2009: 174

Zhao Xu, Kristian Kersting, Volker Tresp: Multi-Relational Learning with Gaussian Processes. IJCAI 2009: 1309-1314

Achim Rettinger, Matthias Nickles, Volker Tresp: Statistical Relational Learning with Formal Ontologies. ECML/PKDD (2) 2009: 286-301

Markus Bundschus, Mathäus Dejori, Martin Stetter, Volker Tresp, Hans-Peter Kriegel: Extraction of semantic biomedical relations from text using conditional random fields. BMC Bioinformatics 9 (2008)

Achim Rettinger, Matthias Nickles, Volker Tresp: A statistical relational model for trust learning. AAMAS (2) 2008: 763-770

Zhao Xu, Volker Tresp, Achim Rettinger, Kristian Kersting: Social Network Mining with Nonparametric Relational Models. SNAKDD 2008: 77-96

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

Volker Tresp, Markus Bundschus, Achim Rettinger, Yi Huang: Towards Machine Learning on the Semantic Web. URSW (LNCS Vol.) 2008: 282-314

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)

Achim Rettinger, Matthias Nickles, Volker Tresp: Learning Initial Trust Among Interacting Agents. CIA 2007: 313-327

Anton Schwaighofer, Mathäus Dejori, Volker Tresp, Martin Stetter: Structure Learning with Nonparametric Decomposable Models. ICANN (1) 2007: 119-128

Shipeng Yu, Volker Tresp, Kai Yu: Robust multi-task learning with t-processes. ICML 2007: 1103-1110

Zhao Xu, Volker Tresp, Shipeng Yu, Kai Yu, Hans-Peter Kriegel: Fast Inference in Infinite Hidden Relational Models. MLG 2007

Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel: Multi-Output Regularized Feature Projection. IEEE Trans. Knowl. Data Eng. 18(12): 1600-1613 (2006)

Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel: Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures. ECML 2006: 841-848

Kai Yu, Jinbo Bi, Volker Tresp: Active learning via transductive experimental design. ICML 2006: 1081-1088

Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel: Collaborative ordinal regression. ICML 2006: 1089-1096

Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel, Mingrui Wu: Supervised probabilistic principal component analysis. KDD 2006: 464-473

Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu: Stochastic Relational Models for Discriminative Link Prediction. NIPS 2006: 1553-1560

Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel: Infinite Hidden Relational Models. UAI 2006

Kai Yu, Shipeng Yu, Volker Tresp: Multi-Output Regularized Projection. CVPR (2) 2005: 597-602

Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, Volker Tresp, Hans-Peter Kriegel: Hierarchy-Regularized Latent Semantic Indexing. ICDM 2005: 178-185

Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Peter Kriegel: Dirichlet enhanced relational learning. ICML 2005: 1004-1011

Kai Yu, Volker Tresp, Anton Schwaighofer: Learning Gaussian processes from multiple tasks. ICML 2005: 1012-1019

Shipeng Yu, Kai Yu, Volker Tresp: Soft Clustering on Graphs. NIPS 2005

Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel: A Probabilistic Clustering-Projection Model for Discrete Data. PKDD 2005: 417-428

Kai Yu, Shipeng Yu, Volker Tresp: Multi-label informed latent semantic indexing. SIGIR 2005: 258-265

Michael Haft, Reimar Hofmann, Volker Tresp: Generative binary codes. Pattern Anal. Appl. 6(4): 269-284 (2004)

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)

Kai Yu, Volker Tresp: Heterogenous Data Fusion via a Probabilistic Latent-Variable Model. ARCS 2004: 20-30

Kai Yu, Shipeng Yu, Volker Tresp: Dirichlet Enhanced Latent Semantic Analysis. LWA 2004: 221-226

Anton Schwaighofer, Volker Tresp, Kai Yu: Learning Gaussian Process Kernels via Hierarchical Bayes. NIPS 2004

Kai Yu, Volker Tresp, Shipeng Yu: A nonparametric hierarchical bayesian framework for information filtering. SIGIR 2004: 353-360

Anton Schwaighofer, Volker Tresp, Peter Mayer, Andreas Krause, Jürgen Beuthan, Helmut Rost, Georg Metzger, Gerhard A. Müller, Alexander K. Scheel: Classification of rheumatoid joint inflammation based on laser imaging. IEEE Trans. Biomed. Engineering 50(3): 375-382 (2003)

Zhao Xu, Xiaowei Xu, Kai Yu, Volker Tresp: A Hybrid Relevance-Feedback Approach to Text Retrieval. ECIR 2003: 281-293

Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi Wang: Representative Sampling for Text Classification Using Support Vector Machines. ECIR 2003: 393-407

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

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

Anton Schwaighofer, Marian Grigoras, Volker Tresp, Clemens Hoffmann: GPPS: A Gaussian Process Positioning System for Cellular Networks. NIPS 2003

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

Kai Yu, Xiaowei Xu, Anton Schwaighofer, Volker Tresp, Hans-Peter Kriegel: Removing redundancy and inconsistency in memory-based collaborative filtering. CIKM 2002: 52-59

Anton Schwaighofer, Volker Tresp: Transductive and Inductive Methods for Approximate Gaussian Process Regression. NIPS 2002: 953-960

Anton Schwaighofer, Volker Tresp, Peter Mayer, Alexander K. Scheel, Gerhard A. Müller: The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging. NIPS 2002: 1409-1416

Volker Tresp: Scaling Kernel-Based Systems to Large Data Sets. Data Min. Knowl. Discov. 5(3): 197-211 (2001)

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

Volker Tresp, Anton Schwaighofer: Scalable Kernel Systems. ICANN 2001: 285-291

Anton Schwaighofer, Volker Tresp: The Bayesian Committee Support Vector Machine. ICANN 2001: 411-420

Todd K. Leen, Thomas G. Dietterich, Volker Tresp (Eds.): Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA. MIT Press 2001

Volker Tresp: A Bayesian Committee Machine. Neural Computation 12(11): 2719-2741 (2000)

Volker Tresp: The generalized Bayesian committee machine. KDD 2000: 130-139

Volker Tresp: Mixtures of Gaussian Processes. NIPS 2000: 654-660

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)

Thomas Briegel, Volker Tresp: Robust Neural Network Regression for Offline and Online Learning. NIPS 1999: 407-413

Volker Tresp, Michael Haft, Reimar Hofmann: Mixture Approximations to Bayesian Networks. UAI 1999: 639-646

Volker Tresp, Reimar Hofmann: Nonlinear Time-Series Prediction with Missing and Noisy Data. Neural Computation 10(3): 731-747 (1998)

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)

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

Jaakko Hollmén, Volker Tresp: Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model. NIPS 1998: 889-895

Volker Tresp, Jürgen Hollatz, Subutai Ahmad: Representing Probabilistic Rules with Networks of Gaussian Basis Functions. Machine Learning 27(2): 173-200 (1997)

Michiaki Taniguchi, Volker Tresp: Averaging Regularized Estimators. Neural Computation 9(5): 1163-1178 (1997)

Michiaki Taniguchi, Volker Tresp: Combining Regularized Neural Networks. ICANN 1997: 349-354

Reimar Hofmann, Volker Tresp: Nonlinear Markov Networks for Continuous Variables. NIPS 1997

Volker Tresp, Thomas Briegel: A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose Prediction. NIPS 1997

Volker Tresp, Ralph Neuneier, Hans-Georg Zimmermann: Early Brain Damage. NIPS 1996: 669-675

Volker Tresp: Die besonderen Eigenschaften Neuronaler Netze bei der Approximation von Funktionen. KI 9(5): 12-17 (1995)

Reimar Hofmann, Volker Tresp: Discovering Structure in Continuous Variables Using Bayesian Networks. NIPS 1995: 500-506

Dirk Ormoneit, Volker Tresp: Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging. NIPS 1995: 542-548

Volker Tresp, Michiaki Taniguchi: Combining Estimators Using Non-Constant Weighting Functions. NIPS 1994: 419-426

Volker Tresp, Ralph Neuneier, Subutai Ahmad: Efficient Methods for Dealing with Missing Data in Supervised Learning. NIPS 1994: 689-696

Volker Tresp, Subutai Ahmad, Ralph Neuneier: Training Neural Networks with Deficient Data. NIPS 1993: 128-135

Jürgen Hollatz, Volker Tresp: Integrating Rule-Based Knowledge into Neural Computing. DAGM-Symposium 1992: 88-95

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

Subutai Ahmad, Volker Tresp: Some Solutions to the Missing Feature Problem in Vision. NIPS 1992: 393-400

Volker Tresp, Jürgen Hollatz, Subutai Ahmad: Network Structuring and Training Using Rule-Based Knowledge. NIPS 1992: 871-878

Volker Tresp: A Neural Architecture for 2D and 3D Vision. DAGM-Symposium 1991: 437-445

Martin Röscheisen, Reimar Hofmann, Volker Tresp: Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency. NIPS 1991: 659-666

Volker Tresp: A Neural Network Approach for Three-Dimensional Object Recognition. NIPS 1990: 306-312