 | 2010 |
| 21 |  | Jan Peters,
Katharina Mülling,
Yasemin Altun:
Relative Entropy Policy Search.
AAAI 2010 |
| 20 |  | 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 |
| 19 |  | 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 |
| 18 |  | Christian Widmer,
Jose Leiva,
Yasemin Altun,
Gunnar Rätsch:
Leveraging Sequence Classification by Taxonomy-Based Multitask Learning.
RECOMB 2010: 522-534 |
| 17 |  | Morteza Alamgir,
Moritz Grosse-Wentrup,
Yasemin Altun:
Multitask Learning for Brain-Computer Interfaces.
Journal of Machine Learning Research - Proceedings Track 9: 17-24 (2010) |
| 16 |  | Ayse Erkan,
Yasemin Altun:
Semi-Supervised Learning via Generalized Maximum Entropy.
Journal of Machine Learning Research - Proceedings Track 9: 209-216 (2010) |
| 2009 |
| 15 |  | 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 |
| 14 |  | Charles Parker,
Yasemin Altun,
Prasad Tadepalli:
Guest editorial: special issue on structured prediction.
Machine Learning 77(2-3): 161-164 (2009) |
| 2007 |
| 13 |  | Qinfeng Shi,
Yasemin Altun,
Alex J. Smola,
S. V. N. Vishwanathan:
Semi-Markov Models for Sequence Segmentation.
EMNLP-CoNLL 2007: 640-648 |
| 2006 |
| 12 |  | Yasemin Altun,
Alexander J. Smola:
Unifying Divergence Minimization and Statistical Inference Via Convex Duality.
COLT 2006: 139-153 |
| 11 |  | Quoc V. Le,
Alexander J. Smola,
Thomas Gärtner,
Yasemin Altun:
Transductive Gaussian Process Regression with Automatic Model Selection.
ECML 2006: 306-317 |
| 10 |  | Massimiliano Ciaramita,
Yasemin Altun:
Broad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger.
EMNLP 2006: 594-602 |
| 2005 |
| 9 |  | Yasemin Altun,
David A. McAllester,
Mikhail Belkin:
Margin Semi-Supervised Learning for Structured Variables.
NIPS 2005 |
| 8 |  | 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) |
| 2004 |
| 7 |  | Michelle L. Gregory,
Yasemin Altun:
Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech.
ACL 2004: 677-683 |
| 6 |  | Yasemin Altun,
Thomas Hofmann,
Alex J. Smola:
Gaussian process classification for segmenting and annotating sequences.
ICML 2004 |
| 5 |  | Ioannis Tsochantaridis,
Thomas Hofmann,
Thorsten Joachims,
Yasemin Altun:
Support vector machine learning for interdependent and structured output spaces.
ICML 2004 |
| 4 |  | Yasemin Altun,
Alexander J. Smola,
Thomas Hofmann:
Exponential Families for Conditional Random Fields.
UAI 2004: 2-9 |
| 2003 |
| 3 |  | Yasemin Altun,
Ioannis Tsochantaridis,
Thomas Hofmann:
Hidden Markov Support Vector Machines.
ICML 2003: 3-10 |
| 2 |  | Yasemin Altun,
Thomas Hofmann:
Large margin methods for label sequence learning.
INTERSPEECH 2003 |
| 2002 |
| 1 |  | Yasemin Altun,
Thomas Hofmann,
Mark Johnson:
Discriminative Learning for Label Sequences via Boosting.
NIPS 2002: 977-984 |