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 | 2012 | |
|---|---|---|
| i1 |      | Yasemin Altun, Alexander J. Smola, Thomas Hofmann: Exponential Families for Conditional Random Fields. CoRR abs/1207.4131 (2012) |
| 2010 | ||
| j5 | | Christian Widmer, Nora C. Toussaint, Yasemin Altun, Gunnar Rätsch: Inferring latent task structure for Multitask Learning by Multiple Kernel Learning. BMC Bioinformatics 11(S-8): S5 (2010) |
| j4 | | Morteza Alamgir, Moritz Grosse-Wentrup, Yasemin Altun: Multitask Learning for Brain-Computer Interfaces. Journal of Machine Learning Research - Proceedings Track 9: 17-24 (2010) |
| j3 | | Ayse Erkan, Yasemin Altun: Semi-Supervised Learning via Generalized Maximum Entropy. Journal of Machine Learning Research - Proceedings Track 9: 209-216 (2010) |
| c17 | | |
| c16 | | Ayse Erkan, Oliver Kroemer, Renaud Detry, Yasemin Altun, Justus H. Piater, Jan Peters: Learning probabilistic discriminative models of grasp affordances under limited supervision. IROS 2010: 1586-1591 |
| c15 | | Christian Widmer, Nora C. Toussaint, Yasemin Altun, Oliver Kohlbacher, Gunnar Rätsch: Novel Machine Learning Methods for MHC Class I Binding Prediction. PRIB 2010: 98-109 |
| c14 | | Christian Widmer, Jose Leiva, Yasemin Altun, Gunnar Rätsch: Leveraging Sequence Classification by Taxonomy-Based Multitask Learning. RECOMB 2010: 522-534 |
| 2009 | ||
| j2 | | Charles Parker, Yasemin Altun, Prasad Tadepalli: Guest editorial: special issue on structured prediction. Machine Learning 77(2-3): 161-164 (2009) |
| c13 | | Daewon Lee, Matthias Hofmann, Florian Steinke, Yasemin Altun, Nathan D. Cahill, Bernhard Schölkopf: Learning similarity measure for multi-modal 3D image registration. CVPR 2009: 186-193 |
| 2007 | ||
| c12 | | Qinfeng Shi, Yasemin Altun, Alex J. Smola, S. V. N. Vishwanathan: Semi-Markov Models for Sequence Segmentation. EMNLP-CoNLL 2007: 640-648 |
| 2006 | ||
| c11 | | Yasemin Altun, Alexander J. Smola: Unifying Divergence Minimization and Statistical Inference Via Convex Duality. COLT 2006: 139-153 |
| c10 | | Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun: Transductive Gaussian Process Regression with Automatic Model Selection. ECML 2006: 306-317 |
| c9 | | Massimiliano Ciaramita, Yasemin Altun: Broad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger. EMNLP 2006: 594-602 |
| 2005 | ||
| j1 | | 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) |
| c8 | | Yasemin Altun, David A. McAllester, Mikhail Belkin: Margin Semi-Supervised Learning for Structured Variables. NIPS 2005 |
| 2004 | ||
| c7 | | Michelle L. Gregory, Yasemin Altun: Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech. ACL 2004: 677-683 |
| c6 | | Yasemin Altun, Thomas Hofmann, Alex J. Smola: Gaussian process classification for segmenting and annotating sequences. ICML 2004 |
| c5 | | Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims, Yasemin Altun: Support vector machine learning for interdependent and structured output spaces. ICML 2004 |
| c4 | | Yasemin Altun, Alexander J. Smola, Thomas Hofmann: Exponential Families for Conditional Random Fields. UAI 2004: 2-9 |
| 2003 | ||
| c3 | | Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofmann: Hidden Markov Support Vector Machines. ICML 2003: 3-10 |
| c2 | | |
| 2002 | ||
| c1 | | Yasemin Altun, Thomas Hofmann, Mark Johnson: Discriminative Learning for Label Sequences via Boosting. NIPS 2002: 977-984 |
Colors in the list of coauthors
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