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Thomas Hofmann: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Thomas Hofmann
    Probabilistic Latent Semantic Indexing. [Citation Graph (1, 0)][DBLP]
    SIGIR, 1999, pp:50-57 [Conf]
  2. Stuart Andrews, Thomas Hofmann, Ioannis Tsochantaridis
    Multiple Instance Learning with Generalized Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2002, pp:943-944 [Conf]
  3. Thomas Hofmann, Justin Basilico
    Collaborative Machine Learning. [Citation Graph (0, 0)][DBLP]
    From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments, 2005, pp:173-182 [Conf]
  4. Lijuan Cai, Thomas Hofmann
    Hierarchical document categorization with support vector machines. [Citation Graph (0, 0)][DBLP]
    CIKM, 2004, pp:78-87 [Conf]
  5. Thomas Hofmann
    From bits and bytes to information and knowledge. [Citation Graph (0, 0)][DBLP]
    CIKM, 2005, pp:3- [Conf]
  6. Kristina Toutanova, Francine Chen, Kris Popat, Thomas Hofmann
    Text Classification in a Hierarchical Mixture Model for Small Training Sets. [Citation Graph (0, 0)][DBLP]
    CIKM, 2001, pp:105-112 [Conf]
  7. Ha Quang Minh, Thomas Hofmann
    Learning Over Compact Metric Spaces. [Citation Graph (0, 0)][DBLP]
    COLT, 2004, pp:239-254 [Conf]
  8. Stéphane Ducasse, Thomas Hofmann, Oscar Nierstrasz
    OpenSpaces: An Object-Oriented Framework for Reconfigurable Coordination Spaces. [Citation Graph (0, 0)][DBLP]
    COORDINATION, 2000, pp:1-18 [Conf]
  9. Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
    Histogram Clustering for Unsupervised Image Segmentation. [Citation Graph (0, 0)][DBLP]
    CVPR, 1999, pp:2602-2608 [Conf]
  10. Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann
    Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval. [Citation Graph (0, 0)][DBLP]
    CVPR, 1997, pp:267-272 [Conf]
  11. Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
    Discrete Mixture Models for Unsupervised Image Segmentation. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 1998, pp:135-142 [Conf]
  12. Thomas Hofmann
    Learning What People (Don't) Want. [Citation Graph (0, 0)][DBLP]
    ECML, 2001, pp:214-225 [Conf]
  13. Ioannis Tsochantaridis, Thomas Hofmann
    Support Vector Machines for Polycategorical Classification. [Citation Graph (0, 0)][DBLP]
    ECML, 2002, pp:456-467 [Conf]
  14. Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
    Deterministic Annealing for Unsupervised Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 1997, pp:213-228 [Conf]
  15. Thomas Hofmann, Joachim M. Buhmann
    An Annealed ``Neural Gas'' Network for Robust Vector Quantization. [Citation Graph (0, 0)][DBLP]
    ICANN, 1996, pp:151-156 [Conf]
  16. David Gondek, Thomas Hofmann
    Non-Redundant Data Clustering. [Citation Graph (0, 0)][DBLP]
    ICDM, 2004, pp:75-82 [Conf]
  17. Thomas Wolf, Benedikt Brors, Thomas Hofmann, Elisabeth Georgii
    Global Biclustering of Microarray Data. [Citation Graph (0, 0)][DBLP]
    ICDM Workshops, 2006, pp:125-129 [Conf]
  18. Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
    An Optimization Approach to Unsupervised Hierarchical Texture Segmentation. [Citation Graph (0, 0)][DBLP]
    ICIP (3), 1997, pp:213-216 [Conf]
  19. Yasemin Altun, Thomas Hofmann, Alex J. Smola
    Gaussian process classification for segmenting and annotating sequences. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  20. Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofmann
    Hidden Markov Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:3-10 [Conf]
  21. Justin Basilico, Thomas Hofmann
    Unifying collaborative and content-based filtering. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  22. Keith Hall, Thomas Hofmann
    Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:351-358 [Conf]
  23. Thomas Navin Lal, Michael Schröder 0002, N. Jeremy Hill, Hubert Preißl, Thilo Hinterberger, Jürgen Mellinger, Martin Bogdan, Wolfgang Rosenstiel, Thomas Hofmann, Niels Birbaumer, Bernhard Schölkopf
    A brain computer interface with online feedback based on magnetoencephalography. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:465-472 [Conf]
  24. Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims, Yasemin Altun
    Support vector machine learning for interdependent and structured output spaces. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  25. Thomas Hofmann
    Probabilistic Topic Maps: Navigating through Large Text Collections. [Citation Graph (0, 0)][DBLP]
    IDA, 1999, pp:161-172 [Conf]
  26. Massimiliano Ciaramita, Thomas Hofmann, Mark Johnson
    Hierarchical Semantic Classification: Word Sense Disambiguation with World Knowledge. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2003, pp:817-822 [Conf]
  27. Thomas Hofmann
    The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1999, pp:682-687 [Conf]
  28. Thomas Hofmann, Jan Puzicha
    Latent Class Models for Collaborative Filtering. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1999, pp:688-693 [Conf]
  29. Lijuan Cai, Thomas Hofmann
    Exploiting Known Taxonomies in Learning Overlapping Concepts. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:714-719 [Conf]
  30. Bhaskar Mehta, Thomas Hofmann, Peter Fankhauser
    Lies and propaganda: detecting spam users in collaborative filtering. [Citation Graph (0, 0)][DBLP]
    Intelligent User Interfaces, 2007, pp:14-21 [Conf]
  31. David Gondek, Thomas Hofmann
    Non-redundant clustering with conditional ensembles. [Citation Graph (0, 0)][DBLP]
    KDD, 2005, pp:70-77 [Conf]
  32. Thomas Hofmann, Joachim M. Buhmann
    Inferring Hierarchical Clustering Structures by Deterministic Annealing. [Citation Graph (0, 0)][DBLP]
    KDD, 1996, pp:363-366 [Conf]
  33. Yasemin Altun, Thomas Hofmann, Mark Johnson
    Discriminative Learning for Label Sequences via Boosting. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:977-984 [Conf]
  34. Stuart Andrews, Thomas Hofmann
    Multiple-Instance Learning via Disjunctive Programming Boosting. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  35. Stuart Andrews, Ioannis Tsochantaridis, Thomas Hofmann
    Support Vector Machines for Multiple-Instance Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:561-568 [Conf]
  36. Joachim M. Buhmann, Thomas Hofmann
    Central and Pairwise Data Clustering by Competitive Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:104-111 [Conf]
  37. David A. Cohn, Thomas Hofmann
    The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:430-436 [Conf]
  38. Thomas Hofmann
    Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:914-920 [Conf]
  39. Thomas Hofmann, Joachim M. Buhmann
    Multidimensional Scaling and Data Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:459-466 [Conf]
  40. Thomas Hofmann, Joachim M. Buhmann
    Active Data Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  41. Thomas Hofmann, Jan Puzicha, Michael I. Jordan
    Learning from Dyadic Data. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:466-472 [Conf]
  42. Dengyong Zhou, Bernhard Schölkopf, Thomas Hofmann
    Semi-supervised Learning on Directed Graphs. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  43. Justin Basilico, Thomas Hofmann
    A joint framework for collaborative and content filtering. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2004, pp:550-551 [Conf]
  44. Lijuan Cai, Thomas Hofmann
    Text categorization by boosting automatically extracted concepts. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2003, pp:182-189 [Conf]
  45. Thomas Hofmann
    Learning probabilistic models of the Web. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2000, pp:369-371 [Conf]
  46. Thomas Hofmann
    Collaborative filtering via gaussian probabilistic latent semantic analysis. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2003, pp:259-266 [Conf]
  47. Thomas Hofmann
    Probabilistic Latent Semantic Analysis. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:289-296 [Conf]
  48. Joachim M. Buhmann, Wolfram Burgard, Armin B. Cremers, Dieter Fox, Thomas Hofmann, Frank E. Schneider, Jiannis Strikos, Sebastian Thrun
    The Mobile Robot RHINO. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 1995, v:16, n:2, pp:31-38 [Journal]
  49. Thomas Hofmann
    ProbMap - A probabilistic approach for mapping large document collections. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2000, v:4, n:2, pp:149-164 [Journal]
  50. Scott Doniger, Thomas Hofmann, Miao-Hui Joanne Yeh
    Predicting CNS Permeability of Drug Molecules: Comparison of Neural Network and Support Vector Machine Algorithms. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2002, v:9, n:6, pp:849- [Journal]
  51. Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, Yasemin Altun
    Large Margin Methods for Structured and Interdependent Output Variables. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:1453-1484 [Journal]
  52. Thomas Hofmann
    Unsupervised Learning by Probabilistic Latent Semantic Analysis. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:42, n:1/2, pp:177-196 [Journal]
  53. Thomas Hofmann, Joachim M. Buhmann
    Pairwise Data Clustering by Deterministic Annealing. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1997, v:19, n:1, pp:1-14 [Journal]
  54. Thomas Hofmann, Joachim M. Buhmann
    Correction to "Pairwise Data Clustering by Deterministic Annealing". [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1997, v:19, n:2, pp:192- [Journal]
  55. Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann
    Unsupervised Texture Segmentation in a Deterministic Annealing Framework. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1998, v:20, n:8, pp:803-818 [Journal]
  56. Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann
    A theory of proximity based clustering: structure detection by optimization. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2000, v:33, n:4, pp:617-634 [Journal]
  57. Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann
    Histogram clustering for unsupervised segmentation and image retrieval. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1999, v:20, n:9, pp:899-909 [Journal]
  58. James Allan, Jay Aslam, Nicholas J. Belkin, Chris Buckley, James P. Callan, W. Bruce Croft, Susan T. Dumais, Norbert Fuhr, Donna Harman, David J. Harper, Djoerd Hiemstra, Thomas Hofmann, Eduard H. Hovy, Wessel Kraaij, John D. Lafferty, Victor Lavrenko, David D. Lewis, Liz Liddy, R. Manmatha, Andrew McCallum, Jay M. Ponte, John M. Prager, Dragomir R. Radev, Philip Resnik, Stephen E. Robertson, Ronald Rosenfeld, Salim Roukos, Mark Sanderson, Rich Schwartz, Amit Singhal, Alan F. Smeaton, Howard R. Turtle, Ellen M. Voorhees, Ralph M. Weischedel, Jinxi Xu, ChengXiang Zhai
    Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002. [Citation Graph (0, 0)][DBLP]
    SIGIR Forum, 2003, v:37, n:1, pp:31-47 [Journal]
  59. Thomas Hofmann
    Latent semantic models for collaborative filtering. [Citation Graph (0, 0)][DBLP]
    ACM Trans. Inf. Syst., 2004, v:22, n:1, pp:89-115 [Journal]
  60. Bhaskar Mehta, Thomas Hofmann
    Cross System Personalization and Collaborative Filtering by Learning Manifold Alignments. [Citation Graph (0, 0)][DBLP]
    KI, 2006, pp:244-259 [Conf]
  61. Yasemin Altun, Alexander J. Smola, Thomas Hofmann
    Exponential Families for Conditional Random Fields. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:2-9 [Conf]
  62. David Gondek, Thomas Hofmann
    Non-redundant data clustering. [Citation Graph (0, 0)][DBLP]
    Knowl. Inf. Syst., 2007, v:12, n:1, pp:1-24 [Journal]

  63. Beyond sliding windows: Object localization by efficient subwindow search. [Citation Graph (, )][DBLP]


  64. Inkrementelle nutzergerechte Etablierung eines Towerlotsen-HMI. [Citation Graph (, )][DBLP]


  65. Robust collaborative filtering. [Citation Graph (, )][DBLP]


  66. Predicting structured objects with support vector machines. [Citation Graph (, )][DBLP]


  67. A Survey of Attack-Resistant Collaborative Filtering Algorithms. [Citation Graph (, )][DBLP]


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