Please note: This is a beta version of the new dblp website.
You can find the classic dblp view of this page here.
You can find the classic dblp view of this page here.
Thomas Hofmann
2010 – today
- 2013
[i2]- 2012
- [i1]Yasemin Altun, Alexander J. Smola, Thomas Hofmann: Exponential Families for Conditional Random Fields. CoRR abs/1207.4131 (2012)
- 2011
- [e3]Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis (Eds.): Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011. Proceedings, Part I. Lecture Notes in Computer Science 6911, Springer 2011, ISBN 978-3-642-23779-9
- [e2]Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis (Eds.): Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part II. Lecture Notes in Computer Science 6912, Springer 2011, ISBN 978-3-642-23782-9
- [e1]Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis (Eds.): Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part III. Lecture Notes in Computer Science 6913, Springer 2011, ISBN 978-3-642-23807-9
2000 – 2009
- 2009
- [j18]Thorsten Joachims, Thomas Hofmann, Yisong Yue, Chun-Nam John Yu: Predicting structured objects with support vector machines. Commun. ACM 52(11): 97-104 (2009)
- [j17]Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann: Efficient Subwindow Search: A Branch and Bound Framework for Object Localization. IEEE Trans. Pattern Anal. Mach. Intell. 31(12): 2129-2142 (2009)
- [c55]Christina König, Thomas Hofmann, Jörg Bergner, Ralph Bruder: Inkrementelle nutzergerechte Etablierung eines Towerlotsen-HMI. Mensch & Computer 2009: 63-72
- 2008
- [j16]Bhaskar Mehta, Thomas Hofmann: A Survey of Attack-Resistant Collaborative Filtering Algorithms. IEEE Data Eng. Bull. 31(2): 14-22 (2008)
- [c54]Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann: Beyond sliding windows: Object localization by efficient subwindow search. CVPR 2008
- 2007
- [j15]
- [j14]Peter Groche, Knut Großmann, Thomas Hofmann, Hajo Wiemer: Advanced experimental and numerical methods for the analysis of the dynamic forming press behavior. Production Engineering 1(3): 303-308 (2007)
- [c53]Lijuan Cai, Thomas Hofmann: Exploiting Known Taxonomies in Learning Overlapping Concepts. IJCAI 2007: 714-719
- [c52]Bhaskar Mehta, Thomas Hofmann, Peter Fankhauser: Lies and propaganda: detecting spam users in collaborative filtering. IUI 2007: 14-21
- [c51]
- 2006
- [c50]Thomas Wolf, Benedikt Brors, Thomas Hofmann, Elisabeth Georgii: Global Biclustering of Microarray Data. ICDM Workshops 2006: 125-129
- [c49]Bhaskar Mehta, Thomas Hofmann: Cross System Personalization and Collaborative Filtering by Learning Manifold Alignments. KI 2006: 244-259
- 2005
- [j13]Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, Yasemin Altun: Large Margin Methods for Structured and Interdependent Output Variables. Journal of Machine Learning Research 6: 1453-1484 (2005)
- [c48]Thomas Hofmann, Justin Basilico: Collaborative Machine Learning. From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments 2005: 173-182
- [c47]
- [c46]Thomas Navin Lal, Michael Schröder, 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. ICML 2005: 465-472
- [c45]
- 2004
- [j12]Thomas Hofmann: Latent semantic models for collaborative filtering. ACM Trans. Inf. Syst. 22(1): 89-115 (2004)
- [c44]Lijuan Cai, Thomas Hofmann: Hierarchical document categorization with support vector machines. CIKM 2004: 78-87
- [c43]
- [c42]
- [c41]Yasemin Altun, Thomas Hofmann, Alex J. Smola: Gaussian process classification for segmenting and annotating sequences. ICML 2004
- [c40]
- [c39]Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims, Yasemin Altun: Support vector machine learning for interdependent and structured output spaces. ICML 2004
- [c38]Dengyong Zhou, Bernhard Schölkopf, Thomas Hofmann: Semi-supervised Learning on Directed Graphs. NIPS 2004
- [c37]Justin Basilico, Thomas Hofmann: A joint framework for collaborative and content filtering. SIGIR 2004: 550-551
- [c36]Yasemin Altun, Alexander J. Smola, Thomas Hofmann: Exponential Families for Conditional Random Fields. UAI 2004: 2-9
- 2003
- [j11]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, Richard M. 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. SIGIR Forum 37(1): 31-47 (2003)
- [c35]Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofmann: Hidden Markov Support Vector Machines. ICML 2003: 3-10
- [c34]Massimiliano Ciaramita, Thomas Hofmann, Mark Johnson: Hierarchical Semantic Classification: Word Sense Disambiguation with World Knowledge. IJCAI 2003: 817-822
- [c33]
- [c32]Stuart Andrews, Thomas Hofmann: Multiple-Instance Learning via Disjunctive Programming Boosting. NIPS 2003
- [c31]Lijuan Cai, Thomas Hofmann: Text categorization by boosting automatically extracted concepts. SIGIR 2003: 182-189
- [c30]Thomas Hofmann: Collaborative filtering via gaussian probabilistic latent semantic analysis. SIGIR 2003: 259-266
- 2002
- [j10]Scott Doniger, Thomas Hofmann, Miao-Hui Joanne Yeh: Predicting CNS Permeability of Drug Molecules: Comparison of Neural Network and Support Vector Machine Algorithms. Journal of Computational Biology 9(6): 849-864 (2002)
- [c29]Stuart Andrews, Thomas Hofmann, Ioannis Tsochantaridis: Multiple Instance Learning with Generalized Support Vector Machines. AAAI/IAAI 2002: 943-944
- [c28]Ioannis Tsochantaridis, Thomas Hofmann: Support Vector Machines for Polycategorical Classification. ECML 2002: 456-467
- [c27]Stuart Andrews, Ioannis Tsochantaridis, Thomas Hofmann: Support Vector Machines for Multiple-Instance Learning. NIPS 2002: 561-568
- [c26]Yasemin Altun, Thomas Hofmann, Mark Johnson: Discriminative Learning for Label Sequences via Boosting. NIPS 2002: 977-984
- 2001
- [j9]Thomas Hofmann: Unsupervised Learning by Probabilistic Latent Semantic Analysis. Machine Learning 42(1/2): 177-196 (2001)
- [c25]Kristina Toutanova, Francine Chen, Kris Popat, Thomas Hofmann: Text Classification in a Hierarchical Mixture Model for Small Training Sets. CIKM 2001: 105-112
- [c24]
- 2000
- [j8]Thomas Hofmann: ProbMap - A probabilistic approach for mapping large document collections. Intell. Data Anal. 4(2): 149-164 (2000)
- [j7]Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann: A theory of proximity based clustering: structure detection by optimization. Pattern Recognition 33(4): 617-634 (2000)
- [c23]Stéphane Ducasse, Thomas Hofmann, Oscar Nierstrasz: OpenSpaces: An Object-Oriented Framework for Reconfigurable Coordination Spaces. COORDINATION 2000: 1-18
- [c22]Keith Hall, Thomas Hofmann: Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval. ICML 2000: 351-358
- [c21]David A. Cohn, Thomas Hofmann: The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity. NIPS 2000: 430-436
- [c20]
1990 – 1999
- 1999
- [j6]Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann: Histogram clustering for unsupervised segmentation and image retrieval. Pattern Recognition Letters 20(9): 899-909 (1999)
- [c19]Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann: Histogram Clustering for Unsupervised Image Segmentation. CVPR 1999: 2602-2608
- [c18]Thomas Hofmann: Probabilistic Topic Maps: Navigating through Large Text Collections. IDA 1999: 161-172
- [c17]Thomas Hofmann: The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data. IJCAI 1999: 682-687
- [c16]
- [c15]
- [c14]Thomas Hofmann: Learning the Similarity of Documents: An Information-Geometric Approach to Document Retrieval and Categorization. NIPS 1999: 914-920
- [c13]
- [c12]
- 1998
- [j5]Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann: Unsupervised Texture Segmentation in a Deterministic Annealing Framework. IEEE Trans. Pattern Anal. Mach. Intell. 20(8): 803-818 (1998)
- [j4]Thomas Hofmann, Joachim M. Buhmann: Competitive learning algorithms for robust vector quantization. IEEE Transactions on Signal Processing 46(6): 1665-1675 (1998)
- [c11]Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann: Discrete Mixture Models for Unsupervised Image Segmentation. DAGM-Symposium 1998: 135-142
- [c10]
- 1997
- [j3]Thomas Hofmann, Joachim M. Buhmann: Pairwise Data Clustering by Deterministic Annealing. IEEE Trans. Pattern Anal. Mach. Intell. 19(1): 1-14 (1997)
- [j2]Thomas Hofmann, Joachim M. Buhmann: Correction to "Pairwise Data Clustering by Deterministic Annealing". IEEE Trans. Pattern Anal. Mach. Intell. 19(2): 192 (1997)
- [c9]Jan Puzicha, Thomas Hofmann, Joachim M. Buhmann: Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval. CVPR 1997: 267-272
- [c8]Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann: Deterministic Annealing for Unsupervised Texture Segmentation. EMMCVPR 1997: 213-228
- [c7]Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann: An Optimization Approach to Unsupervised Hierarchical Texture Segmentation. ICIP (3) 1997: 213-216
- [c6]
- 1996
- [c5]Thomas Hofmann, Joachim M. Buhmann: An Annealed ``Neural Gas'' Network for Robust Vector Quantization. ICANN 1996: 151-156
- [c4]Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann: Unsupervised segmentation of textured images by pairwise data clustering. ICIP (3) 1996: 137-140
- [c3]Thomas Hofmann, Joachim M. Buhmann: Inferring Hierarchical Clustering Structures by Deterministic Annealing. KDD 1996: 363-366
- 1995
- [j1]Joachim M. Buhmann, Wolfram Burgard, Armin B. Cremers, Dieter Fox, Thomas Hofmann, Frank E. Schneider, Jiannis Strikos, Sebastian Thrun: The Mobile Robot RHINO. AI Magazine 16(2): 31-38 (1995)
- 1994
- [c2]Thomas Hofmann, Joachim M. Buhmann: Multidimensional Scaling and Data Clustering. NIPS 1994: 459-466
- 1993
- [c1]Joachim M. Buhmann, Thomas Hofmann: Central and Pairwise Data Clustering by Competitive Neural Networks. NIPS 1993: 104-111
Coauthor Index
data released under the ODC-BY 1.0 license. See also our legal information page
last updated on 2013-02-28 21:00 CET by the dblp team