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Title:
Author:
Volker Tresp: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. 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. [Citation Graph (0, 0)][DBLP]
    AIME, 2001, pp:199-202 [Conf]
  2. Kai Yu, Volker Tresp
    Heterogenous Data Fusion via a Probabilistic Latent-Variable Model. [Citation Graph (0, 0)][DBLP]
    ARCS, 2004, pp:20-30 [Conf]
  3. Kai Yu, Xiaowei Xu, Anton Schwaighofer, Volker Tresp, Hans-Peter Kriegel
    Removing redundancy and inconsistency in memory-based collaborative filtering. [Citation Graph (0, 0)][DBLP]
    CIKM, 2002, pp:52-59 [Conf]
  4. Kai Yu, Shipeng Yu, Volker Tresp
    Multi-Output Regularized Projection. [Citation Graph (0, 0)][DBLP]
    CVPR (2), 2005, pp:597-602 [Conf]
  5. Jürgen Hollatz, Volker Tresp
    Integrating Rule-Based Knowledge into Neural Computing. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 1992, pp:88-95 [Conf]
  6. Martin F. Schlang, Volker Tresp, Klaus Abraham-Fuchs, Wolfgang Härer, P. Weismüller
    Neuronale Netze zur Segmentierung und Clusterung von biomagnetischen Signalen. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 1992, pp:180-185 [Conf]
  7. Volker Tresp
    A Neural Architecture for 2D and 3D Vision. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 1991, pp:437-445 [Conf]
  8. Zhao Xu, Xiaowei Xu, Kai Yu, Volker Tresp
    A Hybrid Relevance-Feedback Approach to Text Retrieval. [Citation Graph (0, 0)][DBLP]
    ECIR, 2003, pp:281-293 [Conf]
  9. Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi Wang
    Representative Sampling for Text Classification Using Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    ECIR, 2003, pp:393-407 [Conf]
  10. Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel
    Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:841-848 [Conf]
  11. Volker Tresp, Kai Yu
    An Introduction to Nonparametric Hierarchical Bayesian Modelling with a Focus on Multi-agent Learning. [Citation Graph (0, 0)][DBLP]
    European Summer School on Multi-AgentControl, 2003, pp:290-312 [Conf]
  12. Anton Schwaighofer, Volker Tresp
    The Bayesian Committee Support Vector Machine. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:411-420 [Conf]
  13. Michiaki Taniguchi, Volker Tresp
    Combining Regularized Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:349-354 [Conf]
  14. Volker Tresp, Anton Schwaighofer
    Scalable Kernel Systems. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:285-291 [Conf]
  15. Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, Volker Tresp, Hans-Peter Kriegel
    Hierarchy-Regularized Latent Semantic Indexing. [Citation Graph (0, 0)][DBLP]
    ICDM, 2005, pp:178-185 [Conf]
  16. Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Peter Kriegel
    Dirichlet enhanced relational learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:1004-1011 [Conf]
  17. Kai Yu, Jinbo Bi, Volker Tresp
    Active learning via transductive experimental design. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:1081-1088 [Conf]
  18. Kai Yu, Volker Tresp, Anton Schwaighofer
    Learning Gaussian processes from multiple tasks. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:1012-1019 [Conf]
  19. Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel
    Collaborative ordinal regression. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:1089-1096 [Conf]
  20. Volker Tresp
    The generalized Bayesian committee machine. [Citation Graph (0, 0)][DBLP]
    KDD, 2000, pp:130-139 [Conf]
  21. Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel, Mingrui Wu
    Supervised probabilistic principal component analysis. [Citation Graph (0, 0)][DBLP]
    KDD, 2006, pp:464-473 [Conf]
  22. Kai Yu, Shipeng Yu, Volker Tresp
    Dirichlet Enhanced Latent Semantic Analysis. [Citation Graph (0, 0)][DBLP]
    LWA, 2004, pp:221-226 [Conf]
  23. 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. [Citation Graph (0, 0)][DBLP]
    ACM Multimedia, 2003, pp:622-631 [Conf]
  24. Subutai Ahmad, Volker Tresp
    Some Solutions to the Missing Feature Problem in Vision. [Citation Graph (0, 0)][DBLP]
    NIPS, 1992, pp:393-400 [Conf]
  25. Thomas Briegel, Volker Tresp
    Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:403-409 [Conf]
  26. Thomas Briegel, Volker Tresp
    Robust Neural Network Regression for Offline and Online Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:407-413 [Conf]
  27. Reimar Hofmann, Volker Tresp
    Discovering Structure in Continuous Variables Using Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:500-506 [Conf]
  28. Reimar Hofmann, Volker Tresp
    Nonlinear Markov Networks for Continuous Variables. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  29. Jaakko Hollmén, Volker Tresp
    Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:889-895 [Conf]
  30. Dirk Ormoneit, Volker Tresp
    Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:542-548 [Conf]
  31. Martin Röscheisen, Reimar Hofmann, Volker Tresp
    Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:659-666 [Conf]
  32. Anton Schwaighofer, Marian Grigoras, Volker Tresp, Clemens Hoffmann
    GPPS: A Gaussian Process Positioning System for Cellular Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  33. Anton Schwaighofer, Volker Tresp
    Transductive and Inductive Methods for Approximate Gaussian Process Regression. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:953-960 [Conf]
  34. Anton Schwaighofer, Volker Tresp, Peter Mayer, Alexander K. Scheel, Gerhard Müller
    The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:1409-1416 [Conf]
  35. Anton Schwaighofer, Volker Tresp, Kai Yu
    Learning Gaussian Process Kernels via Hierarchical Bayes. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  36. Volker Tresp
    Mixtures of Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:654-660 [Conf]
  37. Volker Tresp
    A Neural Network Approach for Three-Dimensional Object Recognition. [Citation Graph (0, 0)][DBLP]
    NIPS, 1990, pp:306-312 [Conf]
  38. Volker Tresp, Subutai Ahmad, Ralph Neuneier
    Training Neural Networks with Deficient Data. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:128-135 [Conf]
  39. Volker Tresp, Thomas Briegel
    A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose Prediction. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  40. Volker Tresp, Jürgen Hollatz, Subutai Ahmad
    Network Structuring and Training Using Rule-Based Knowledge. [Citation Graph (0, 0)][DBLP]
    NIPS, 1992, pp:871-878 [Conf]
  41. Volker Tresp, Ralph Neuneier, Subutai Ahmad
    Efficient Methods for Dealing with Missing Data in Supervised Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:689-696 [Conf]
  42. Volker Tresp, Ralph Neuneier, Hans-Georg Zimmermann
    Early Brain Damage. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:669-675 [Conf]
  43. Volker Tresp, Michiaki Taniguchi
    Combining Estimators Using Non-Constant Weighting Functions. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:419-426 [Conf]
  44. Shipeng Yu, Kai Yu, Volker Tresp
    Soft Clustering on Graphs. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  45. Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel
    A Probabilistic Clustering-Projection Model for Discrete Data. [Citation Graph (0, 0)][DBLP]
    PKDD, 2005, pp:417-428 [Conf]
  46. Kai Yu, Volker Tresp, Shipeng Yu
    A nonparametric hierarchical bayesian framework for information filtering. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2004, pp:353-360 [Conf]
  47. Kai Yu, Shipeng Yu, Volker Tresp
    Multi-label informed latent semantic indexing. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2005, pp:258-265 [Conf]
  48. Volker Tresp, Michael Haft, Reimar Hofmann
    Mixture Approximations to Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:639-646 [Conf]
  49. Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang
    Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:616-623 [Conf]
  50. Volker Tresp
    Scaling Kernel-Based Systems to Large Data Sets. [Citation Graph (0, 0)][DBLP]
    Data Min. Knowl. Discov., 2001, v:5, n:3, pp:197-211 [Journal]
  51. Volker Tresp
    Die besonderen Eigenschaften Neuronaler Netze bei der Approximation von Funktionen. [Citation Graph (0, 0)][DBLP]
    KI, 1995, v:9, n:5, pp:12-17 [Journal]
  52. Volker Tresp, Jürgen Hollatz, Subutai Ahmad
    Representing Probabilistic Rules with Networks of Gaussian Basis Functions. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:27, n:2, pp:173-200 [Journal]
  53. Michiaki Taniguchi, Volker Tresp
    Averaging Regularized Estimators. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:5, pp:1163-1178 [Journal]
  54. Volker Tresp
    A Bayesian Committee Machine. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:11, pp:2719-2741 [Journal]
  55. Volker Tresp, Reimar Hofmann
    Nonlinear Time-Series Prediction with Missing and Noisy Data. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1998, v:10, n:3, pp:731-747 [Journal]
  56. Michael Haft, Reimar Hofmann, Volker Tresp
    Generative binary codes. [Citation Graph (0, 0)][DBLP]
    Pattern Anal. Appl., 2004, v:6, n:4, pp:269-284 [Journal]
  57. Kai Yu, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, Hans-Peter Kriegel
    Probabilistic Memory-Based Collaborative Filtering. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Knowl. Data Eng., 2004, v:16, n:1, pp:56-69 [Journal]
  58. Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel
    Multi-Output Regularized Feature Projection. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Knowl. Data Eng., 2006, v:18, n:12, pp:1600-1613 [Journal]
  59. Achim Rettinger, Matthias Nickles, Volker Tresp
    Learning Initial Trust Among Interacting Agents. [Citation Graph (0, 0)][DBLP]
    CIA, 2007, pp:313-327 [Conf]
  60. Anton Schwaighofer, Mathäus Dejori, Volker Tresp, Martin Stetter
    Structure Learning with Nonparametric Decomposable Models. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2007, pp:119-128 [Conf]
  61. Shipeng Yu, Volker Tresp, Kai Yu
    Robust multi-task learning with t-processes. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:1103-1110 [Conf]
  62. Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu
    Stochastic Relational Models for Discriminative Link Prediction. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1553-1560 [Conf]
  63. Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel
    Infinite Hidden Relational Models. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]

  64. A statistical relational model for trust learning. [Citation Graph (, )][DBLP]


  65. Hierarchical Bayesian Models for Collaborative Tagging Systems. [Citation Graph (, )][DBLP]


  66. Tutorial summary: Learning with dependencies between several response variables. [Citation Graph (, )][DBLP]


  67. Multi-Relational Learning with Gaussian Processes. [Citation Graph (, )][DBLP]


  68. Social Network Mining with Nonparametric Relational Models. [Citation Graph (, )][DBLP]


  69. Statistical Relational Learning with Formal Ontologies. [Citation Graph (, )][DBLP]


  70. Towards Machine Learning on the Semantic Web. [Citation Graph (, )][DBLP]


  71. Fast Inference in Infinite Hidden Relational Models. [Citation Graph (, )][DBLP]


  72. Towards LarKC: A Platform for Web-Scale Reasoning. [Citation Graph (, )][DBLP]


  73. Extraction of semantic biomedical relations from text using conditional random fields. [Citation Graph (, )][DBLP]


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