Publikationen von T Hofmann

Lampert, C.; Blaschko, M.; Hofmann, T.: Efficient Subwindow Search: A Branch and Bound Framework for Object Localization. IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (12), S. 2129 - 2142 (2009)

Hofmann, T.; Schölkopf, B.; Smola, A.: Kernel Methods in Machine Learning. The Annals of Statistics 36 (3), S. 1171 - 1220 (2008)

Tsochantaridis, I.; Joachims, T.; Hofmann, T.; Altun, Y.: Large Margin Methods for Structured and Interdependent Output Variables. The Journal of Machine Learning Research 6, S. 1453 - 1484 (2005)

Bakir, G.; Hofmann, T.; Schölkopf, B.; Smola , A.; Taskar, B.; Vishwanathan, S.: Predicting Structured Data. MIT Press, Cambridge, MA, USA (2007), 360 S.

Altun, Y.; Hofmann, T.; Tsochantaridis, I.: Support Vector Machine Learning for Interdependent and Structured Output Spaces. In: Predicting Structured Data, S. 85 - 104 (Hg. Bakır, G.; Hofmann, T.; Schölkopf, B.; Smola, A.; Taskar, B. et al.). MIT Press, Cambridge, MA, USA (2007)

Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference. Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), Vancouver, BC, Canada, 04. Dezember 2007 - 07. Dezember 2007. (2007), 1690 S.

Lampert, C.; Blaschko, M.; Hofmann, T.: Beyond Sliding Windows: Object Localization by Efficient Subwindow Search. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, S. 1 - 8. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, AK, USA, 23. Juni 2008 - 28. Juni 2008. IEEE, Piscataway, NJ, USA (2008)

Blaschko, M.; Hofmann, T.: Conformal Multi-Instance Kernels. In: NIPS 2006 Workshop on Learning to Compare Examples, S. 1 - 6. NIPS 2006 Workshop on Learning to Compare Examples, Whistler, BC, Canada, 08. Dezember 2006. (2006)

Wolf, T.; Brors, B.; Hofmann, T.; Georgii, E.: Global Biclustering of Microarray Data. In: Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), S. 125 - 129 (Hg. Tsumoto, S.; Clifton, C.; Zhong, N.; Wu, X.; Liu, J. et al.). Sixth IEEE International Conference on Data Mining Workshops (ICDMW 2006), Hong Kong, China, 18. Dezember 2006 - 22. Dezember 2006. IEEE Computer Society, Los Alamitos, CA, USA (2006)

Lal, T.; Schröder, M.; Hill, J.; Preissl, H.; Hinterberger, T.; Meilinger, J.; Bogdan, M.; Rosenstiel, W.; Hofmann, T.; Birbaumer, N. et al.; Schölkopf, B.: A Brain Computer Interface with Online Feedback based on Magnetoencephalography. In: ICML '05: 22nd international conference on Machine learning, S. 465 - 472 (Hg. Dzeroski, S.; de Raedt, L.; Wrobel, S.). 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, 07. August 2008 - 11. August 2008. ACM Press, New York, NY, USA (2005)

Zhou, D.; Schölkopf, B.; Hofmann, T.: Semi-supervised Learning on Directed Graphs. In: Advances in Neural Information Processing Systems 17, S. 1633 - 1640 (Hg. Saul, L.; Weiss, Y.; Bottou, L.). Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), Vancouver, BC, Canada, 13. Dezember 2004 - 16. Dezember 2004. MIT Press, Cambridge, MA, USA (2005)

Altun, Y.; Hofmann, T.; Smola, A.: Gaussian Process Classification for Segmenting and Annotating Sequences. In: ICML '04: Twenty-First International Conference on Machine Learning, 4, S. 25 - 32 (Hg. Greiner, R.; Schuurmans, D.). Twenty-First International Conference on Machine Learning (ICML 2004), Banff, Canada, 04. Juli 2004 - 08. Juli 2004. ACM Press, New York, USA (2004)

Altun, Y.; Smola, A.; Hofmann, T.: Exponential Families for Conditional Random Fields. In: UAI '04: 20th Annual Conference on Uncertainty in Artificial Intelligence, S. 2 - 9 (Hg. Meek, C.; Chickering, M.; Halpern, J.). 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI 2004), Banff, Canada, 07. Juli 2004 - 11. Juli 2004. ACM Press, New York, NY, USA (2004)

Tsochantaridis, I.; Hofmann, T.; Joachims, T.; Altun, Y.: Support vector machine learning for interdependent and structured output spaces. In: ICML '04: Twenty-first International Conference on Machine Learning, 104, S. 823 - 830 (Hg. Greiner, R.; Schuurmans, D.). Twenty-first International Conference on Machine Learning (ICML 2004), Banff, Canada, 04. Juli 2004 - 08. Juli 2004. ACM Press, New York, NY, USA (2004)

Basilico, J.; Hofmann, T.: Unifying Colloborative and Content-Based Filtering. ICLM 2004, Banff, Alberta, Canada. Proceedings of the 21st International Conference on Machine Learning, S. 65 (2004)

Altun, Y.; Hofmann, T.: Large Margin Methods for Label Sequence Learning. In: 8th European Conference on Speech Communication and Technology (EUROSPEECH 2003), S. 993 - 996. 8th European Conference on Speech Communication and Technology (EUROSPEECH 2003), Genf, Switzerland, 01. September 2003 - 04. September 2003. International Speech Communication Association, Bonn, Germany (2003)

Altun, Y.; Hofmann, T.; Johnson, M.: Discriminative Learning for Label Sequences via Boosting. In: Advances in Neural Information Processing Systems 15, S. 977 - 984 (Hg. Becker, S.; Thrun, S.; Obermayer, K.). Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), Vancouver, BC, Canada, 09. Dezember 2002 - 14. Dezember 2002. MIT Press, Cambridge, MA, USA (2003)

Altun, Y.; Tsochantaridis, I.; Hofmann, T.: Hidden Markov Support Vector Machines. In: Twentieth International Conference on Machine Learning (ICML 2003), S. 4 - 11 (Hg. Fawcett, T.; Mishra, N.). Twentieth International Conference on Machine Learning (ICML 2003), Washington, DC, USA, 21. August 2003 - 24. August 2003. AAAI Press, Menlo Park, CA, USA (2003)

Blaschko, M.; Hofmann, T.; Lampert, C.: Efficient Subwindow Search for Object Localization (Technical Report of the Max Planck Institute for Biological Cybernetics, 164). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 14 S.