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127 Publications
2011 | Published | Journal Article | IST-REx-ID: 3382
Kroemer, O., Lampert, C., & Peters, J. (2011). Learning dynamic tactile sensing with robust vision based training. IEEE Transactions on Robotics. IEEE. https://doi.org/10.1109/TRO.2011.2121130
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| DOI
2011 | Published | Journal Article | IST-REx-ID: 3389
Blaschko, M., Shelton, J., Bartels, A., Lampert, C., & Gretton, A. (2011). Semi supervised kernel canonical correlation analysis with application to human fMRI. Pattern Recognition Letters. Elsevier. https://doi.org/10.1016/j.patrec.2011.02.011
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| DOI
2011 | Published | Conference Paper | IST-REx-ID: 3163
Lampert, C. (2011). Maximum margin multi-label structured prediction. Presented at the NIPS: Neural Information Processing Systems, Granada, Spain: Neural Information Processing Systems Foundation.
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2011 | Published | Conference Poster | IST-REx-ID: 3322
Lampert, C. (2011). Maximum margin multi label structured prediction. NIPS: Neural Information Processing Systems. Neural Information Processing Systems Foundation.
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2011 | Published | Conference Paper | IST-REx-ID: 3337
Wang, Z., Lampert, C., Mülling, K., Schölkopf, B., & Peters, J. (2011). Learning anticipation policies for robot table tennis (pp. 332–337). Presented at the IROS: Intelligent Robots and Systems, San Francisco, USA: IEEE. https://doi.org/10.1109/IROS.2011.6094892
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2010 | Published | Conference Paper | IST-REx-ID: 3793 | 
Nowozin, S., Gehler, P., & Lampert, C. (2010). On parameter learning in CRF-based approaches to object class image segmentation (Vol. 6316, pp. 98–111). Presented at the ECCV: European Conference on Computer Vision, Heraklion, Crete, Greece: Springer. https://doi.org/10.1007/978-3-642-15567-3_8
[Submitted Version]
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2010 | Published | Conference Paper | IST-REx-ID: 3794
Lampert, C., & Krömer, O. (2010). Weakly-paired maximum covariance analysis for multimodal dimensionality reduction and transfer learning. In 11th European Conference on Computer Vision (Vol. 6312, pp. 566–579). Heraklion, Crete, Greece: Springer. https://doi.org/10.1007/978-3-642-15552-9_41
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