Employee

May 2012
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Thomas Hofmann

Position: Research Scientist Unit: Alumni Schölkopf

Publications

Books (1):
•	Bakir GH , Hofmann T , Schölkopf B , Smola AJ , Taskar B and Vishwanathan SVN : Predicting Structured Data, 360, MIT Press, Cambridge, MA, USA, (September-2007).
Proceedings (1):
•	Schölkopf B , Platt J and Hofmann T : Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference, Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), 1690, MIT Press, Cambridge, MA, USA, (September-2007). 0-262-19568-2
Articles (3):
•	Lampert CH , Blaschko MB and Hofmann T (December-2009) Efficient Subwindow Search: A Branch and Bound Framework for Object Localization IEEE Transactions on Pattern Analysis and Machine Intelligence 31(12) 2129-2142.
•	Hofmann T , Schölkopf B and Smola AJ (June-2008) Kernel Methods in Machine Learning Annals of Statistics 36(3) 1171-1220.
•	Tsochantaridis I , Joachims T , Hofmann T and Altun Y (September-2005) Large Margin Methods for Structured and Interdependent Output Variables Journal of Machine Learning Research 6 1453-1484.
Conference papers (13):
•	Lampert CH , Blaschko MB and Hofmann T (June-2008) Beyond Sliding Windows: Object Localization by Efficient Subwindow Search In: CVPR 2008, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, Los Alamitos, CA, USA, 1-8.
•	Blaschko MB and Hofmann T (December-2006) Conformal Multi-Instance Kernels NIPS 2006 Workshop on Learning to Compare Examples, 1-6.
•	Wolf T , Brors B , Hofmann T and Georgii E (December-2006) Global Biclustering of Microarray Data In: ICDMW 2006, Sixth IEEE International Conference on Data Mining, IEEE Computer Society, Los Alamitos, CA, USA, 125-129.
•	Zhou D , Schölkopf B and Hofmann T (July-2005) Semi-supervised Learning on Directed Graphs In: Advances in Neural Information Processing Systems 17, Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), MIT Press, Cambridge, MA, USA, 1633-1640.
•	Lal TN , Schröder M , Hill J , Preissl H , Hinterberger T , Mellinger J , Bogdan M , Rosenstiel W , Hofmann T , Birbaumer N and Schölkopf B (2005) A Brain Computer Interface with Online Feedback based on Magnetoencephalography ICML Bonn, 465.
•	Altun Y , Smola AJ and Hofmann T (July-2004) Exponential Families for Conditional Random Fields 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI 2004), Morgan Kaufmann, San Francisco, CA, USA, 2-9.
•	Altun Y , Hofmann T and Smola AJ (July-2004) Gaussian Process Classification for Segmenting and Annotating Sequences 21st International Conference on Machine Learning (ICML 2004), ACM Press, New York, USA, 25-32.
•	Tsochantaridis I , Hofmann T , Joachims T and Altun Y (July-2004) Support vector machine learning for interdependent and structured output spaces Twenty-first International Conference on Machine Learning (ICML 2004), AAAI Press, Menlo Park, CA, USA, 1-8.
•	Basilico J and Hofmann T (2004) Unifying Colloborative and Content-Based Filtering. In: ACM International Conference Proceeding Series, ICLM 2004, ACM Press, New York, USA, 65.
•	Altun Y , Hofmann T and Johnson M (October-2003) Discriminative Learning for Label Sequences via Boosting In: Advances in Neural Information Processing Systems 15, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 977-984.
•	Altun Y and Hofmann T (September-2003) Large Margin Methods for Label Sequence Learning 8th European Conference on Speech Communication and Technology (EuroSpeech 2003), International Speech Communication Association, Bonn, Germany, 993-996.
•	Altun Y , Tsochantaridis I and Hofmann T (August-2003) Hidden Markov Support Vector Machines Twentieth International Conference on Machine Learning (ICML 2003), AAAI Press, Menlo Park, CA, USA, 4-11.
•	Altun Y , Johnson M and Hofmann T (July-2003) Loss Functions and Optimization Methods for Discriminative Learning of Label Sequences Conference on Empirical Methods in Natural Language Processing (EMNLP 2003), ACL, East Stroudsburg, PA, USA, 145-152.
Contributions to books (1):
•	Altun Y , Hofmann T and Tsochantaridis I : Support Vector Machine Learning for Interdependent and Structured Output Spaces, 85-104. In: Predicting Structured Data, (Ed) G. H. BakIr, MIT Press, Cambridge, MA, USA, (September-2007).
Technical reports (1):
•	Blaschko MB , Hofmann T and Lampert CH : Efficient Subwindow Search for Object Localization, 164, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (August-2007).