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Nobody
Yasemin Altun
Dr. (Brown University, USA)
Position: Senior Research Scientist
Room no.: 223
Phone: +49 7071 601 1613
Fax: +49 7071 601 552

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2011
Articles
2010
Articles
  • C. Widmer, NC. Toussaint, Y. Altun, G. Rätsch (2010). Inferring latent task structure for Multitask Learning by Multiple Kernel Learning BMC Bioinformatics, 11 Suppl 8, S5
Conference Papers
  • AN. Erkan, G. Camps-Valls, Y. Altun (2010). Semi-supervised Remote Sensing Image Classification via Maximum Entropy Proceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010), IEEE, Institute of Electrical and Electronics Engineers, Piscataway, NJ, USA, 313-318, 2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010)
  • C. Widmer, NC. Toussaint, Y. Altun, O. Kohlbacher, G. Rätsch (2010). Novel machine learning methods for MHC Class I binding prediction In: Pattern Recognition in Bioinformatics, (Ed) TMH Dijkstra and E Tsivtsivadze and E Marchiori and T Heskes, Springer, Berlin, Germany, 98–109, 5th IAPR International Conference, PRIB 2010
  • M. Alamgir, M. Grosse-Wentrup, Y. Altun (2010). Multitask Learning for Brain-Computer Interfaces In: JMLR Workshop and Conference Proceedings Volume 9: AISTATS 2010, (Ed) Teh, Y.W. , M. Titterington, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010), JMLR, Cambridge, MA, USA, 17-24, Thirteenth International Conference on Artificial Intelligence and Statistics
  • AN. Erkan, O. Kroemer, R. Detry, Y. Altun, J. Piater, J. Peters (2010). Learning Probabilistic Discriminative Models of Grasp Affordances under Limited Supervision Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), IEEE, Piscataway, NJ, USA, 1586-1591, ISBN: 978-1-424-46675-7, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)
  • J. Peters, K. Mülling, Y. Altun (2010). Relative Entropy Policy Search (Ed) Fox, M. , D. Poole, Proceedings of the Twenty-Fourth National Conference on Artificial Intelligence, AAAI Press, Association for the Advancement of Artificial Intelligence, Menlo Park, CA, USA, 1607-1612, ISBN: 978-1-577-35463-5, Twenty-Fourth National Conference on Artificial Intelligence (AAAI-10)
  • AN. Erkan, Y. Altun (2010). Semi-supervised Learning via Generalized Maximum Entropy In: JMLR Workshop and Conference Proceedings Volume 9: AISTATS 2010, (Ed) Teh, Y.W. , M. Titterington, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010), JMLR, Cambridge, MA, USA, 209-216, Thirteenth International Conference on Artificial Intelligence and Statistics
  • C. Widmer, J. Leiva, Y. Altun, G. Rätsch (2010). Leveraging Sequence Classification by Taxonomy-based Multitask Learning In: Research in Computational Molecular Biology, LNCS, Vol. 6044, (Ed) B Berger, Springer, Berlin, Germany, 522–534, 14th Annual International Conference, RECOMB 2010
Posters
  • AN. Erkan, Y. Altun (2010). A Maximum Entropy Approach to Semi-supervised Learning 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, 80
  • J. Peters, K. Mülling, Y. Altun (2010). Reinforcement Learning by Relative Entropy Policy Search 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, 69
Contributions to books
2009
Articles
  • C. Parker, Y. Altun, P. Tadepalli (2009). Guest editorial: special issue on structured prediction Machine Learning, 77, (2-3), 161-164
Conference Papers
  • D. Lee, M. Hofmann, F. Steinke, Y. Altun, ND. Cahill, B. Schölkopf (2009). Learning the Similarity Measure for Multi-Modal 3D Image Registration Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), IEEE Service Center, Piscataway, NJ, USA, 186-193, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009)
Contributions to books
  • Y. Altun (2009). Large Margin Methods for Part of Speech Tagging In: Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, (Ed) Keshet, J. , S. Bengio, Wiley, Hoboken, NJ, USA, 141-160, ISBN: 978-0-470-69683-5
2007
Contributions to books
  • Altun, Y. and Smola, AJ. (2007). Density Estimation of Structured Outputs in Reproducing Kernel Hilbert Spaces In: Predicting Structured Data, (Ed) BakIr, G. H., T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar, S. V.N. Vishwanathan, MIT Press, Cambridge, MA, USA, 283-300, ISBN: 978-0-262-02617-8
  • Y. Altun, T. Hofmann, I. Tsochantaridis (2007). Support Vector Machine Learning for Interdependent and Structured Output Spaces In: Predicting Structured Data, (Ed) Bakir, G. H. , T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar, S. V. N. Vishwanathan, MIT Press, Cambridge, MA, USA, 85-104, ISBN: 978-0-262-02617-8
  • Altun, Y. and Hofmann, T. and Tsochantaridis, I. (2007). Support Vector Machine Learning for Interdependent and Structured Output Spaces In: Predicting Structured Data, (Ed) BakIr, G. H., T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar, S. V.N. Vishwanathan, MIT Press, Cambridge, MA, USA, 85-104, ISBN: 978-0-262-02617-8
2006
Conference Papers
  • Le, QV. and Smola, AJ. and Gärtner, T. and Altun, Y. (2006). Transductive Gaussian Process Regression with Automatic Model Selection (Ed) Fürnkranz, J. , T. Scheffer, M. Spiliopoulou, Machine Learning: ECML 2006, Springer, Berlin, Germany, 306-317, 17th European Conference on Machine Learning (ECML 2006)
  • Altun, Y. and Smola, AJ. (2006). Unifying Divergence Minimization and Statistical Inference Via Convex Duality In: Learning Theory, (Ed) Lugosi, G. , H.-U. Simon, Learning Theory: 19th Annual Conference on Learning Theory (COLT 2006), Springer, Berlin, Germany, 139-153, 19th Annual Conference on Learning Theory (COLT 2006)
  • Ciaramita, M. and Altun, Y. (2006). Broad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger (Ed) Jurafsky, D. , E. Gaussier, Association for Computational Linguistics, Stroudsburg, PA, USA, 594-602, 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP 2006)
  • Altun, Y. and McAllester, DA. and Belkin, M. (2006). Maximum Margin Semi-Supervised Learning for Structured Variables In: Advances in neural information processing systems 18, (Ed) Weiss, Y. , B. Schölkopf, J. Platt, Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference, MIT Press, Cambridge, MA, USA, 33-40, ISBN: 0-262-23253-7, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005)
2005
Theses
  • Altun, Y. (2005). Discriminative Methods for Label Sequence Learning Brown University, Providence, RI, USA
Articles
  • Tsochantaridis, I. and Joachims, T. and Hofmann, T. and Altun, Y. (2005). Large Margin Methods for Structured and Interdependent Output Variables Journal of Machine Learning Research, 6, 1453-1484
2004
Conference Papers
  • Y. Altun, AJ. Smola, T. Hofmann (2004). Exponential Families for Conditional Random Fields (Ed) Chickering, D.M. , J.Y. Halpern, Proceedings of the 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI 2004), Morgan Kaufmann, San Francisco, CA, USA, 2-9, ISBN: 0-9749039-0-6, 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI 2004)
  • Tsochantaridis, I. and Hofmann, T. and Joachims, T. and Altun, Y. (2004). Support vector machine learning for interdependent and structured output spaces (Ed) Greiner, R. , D. Schuurmans, AAAI Press, Menlo Park, CA, USA, 1-8, Twenty-first International Conference on Machine Learning (ICML 2004)
  • Gregory, M. and Altun, Y. (2004). Using Conditional Random Fields to Predict Pitch Accent in Conversational Speech (Ed) Scott, D. , W. Daelemans, M. Walker, ACL, East Stroudsburg, PA, USA, 677-684, ISBN: 1-932432-34-5, 42nd Annual Meeting of the Association for Computational Linguistics (ACL 2004)
  • Altun, Y. and Hofmann, T. and Smola, AJ. (2004). Gaussian Process Classification for Segmenting and Annotating Sequences (Ed) Greiner, R. , D. Schuurmans, Proceedings of the 21st International Conference on Machine Learning (ICML 2004), ACM Press, New York, USA, 25-32, 21st International Conference on Machine Learning (ICML 2004)
2003
Conference Papers
  • Altun, Y. and Tsochantaridis, I. and Hofmann, T. (2003). Hidden Markov Support Vector Machines (Ed) Fawcett, T. , N. Mishra, AAAI Press, Menlo Park, CA, USA, 4-11, ISBN: 9781577351894, Twentieth International Conference on Machine Learning (ICML 2003)
  • Altun, Y. and Johnson, M. and Hofmann, T. (2003). Loss Functions and Optimization Methods for Discriminative Learning of Label Sequences (Ed) Collins, M. , M. Steedman, ACL, East Stroudsburg, PA, USA, 145-152, Conference on Empirical Methods in Natural Language Processing (EMNLP 2003)
  • Altun, Y. and Hofmann, T. (2003). Large Margin Methods for Label Sequence Learning International Speech Communication Association, Bonn, Germany, 993-996, 8th European Conference on Speech Communication and Technology (EuroSpeech 2003)
  • Altun, Y. and Hofmann, T. and Johnson, M. (2003). Discriminative Learning for Label Sequences via Boosting In: Advances in Neural Information Processing Systems 15, (Ed) Becker, S. , S. Thrun, K. Obermayer , MIT Press, Cambridge, MA, USA, 977-984, ISBN: 978-0-262-02550-8 , Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002)
Theses
  • Altun, Y. (2003). Large margin Methods in Label Sequence Learning Brown University, Providence, RI, USA
1999
Theses
  • Altun, Y. (1999). Machine Learning and Language Acquisition: A Model of Child’s Learning of Turkish Morphophonology Middle East Technical University, Ankara, Turkey