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114 Publications
2015 | Conference Paper | IST-REx-ID: 12881 | 
Martius GS, Olbrich E. Quantifying self-organizing behavior of autonomous robots. In: Proceedings of the 13th European Conference on Artificial Life. MIT Press; 2015:78. doi:10.7551/978-0-262-33027-5-ch018
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2015 | Thesis | IST-REx-ID: 1401 |
Sharmanska V. Learning with attributes for object recognition: Parametric and non-parametrics views. 2015. doi:10.15479/at:ista:1401
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2015 | Journal Article | IST-REx-ID: 1655 |
Martius GS, Olbrich E. Quantifying emergent behavior of autonomous robots. Entropy. 2015;17(10):7266-7297. doi:10.3390/e17107266
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2014 | Book Chapter | IST-REx-ID: 1829
Muelling K, Kroemer O, Lampert C, Schölkopf B. Movement templates for learning of hitting and batting. In: Kober J, Peters J, eds. Learning Motor Skills. Vol 97. From Algorithms to Robot Experiments. Springer; 2014:69-82. doi:10.1007/978-3-319-03194-1_3
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2014 | Conference Paper | IST-REx-ID: 2033 |
Hernandez Lobato D, Sharmanska V, Kersting K, Lampert C, Quadrianto N. Mind the nuisance: Gaussian process classification using privileged noise. In: Advances in Neural Information Processing Systems. Vol 1. Neural Information Processing Systems; 2014:837-845.
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2014 | Conference Paper | IST-REx-ID: 2057 |
Morvant E, Habrard A, Ayache S. Majority vote of diverse classifiers for late fusion. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8621. Springer; 2014:153-162. doi:10.1007/978-3-662-44415-3_16
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2014 | Conference Paper | IST-REx-ID: 2171 |
Kolesnikov A, Guillaumin M, Ferrari V, Lampert C. Closed-form approximate CRF training for scalable image segmentation. In: Fleet D, Pajdla T, Schiele B, Tuytelaars T, eds. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8691. Springer; 2014:550-565. doi:10.1007/978-3-319-10578-9_36
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2014 | Conference Paper | IST-REx-ID: 2173 |
Khamis S, Lampert C. CoConut: Co-classification with output space regularization. In: Proceedings of the British Machine Vision Conference 2014. BMVA Press; 2014.
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2014 | Conference Paper | IST-REx-ID: 2172
Sydorov V, Sakurada M, Lampert C. Deep Fisher Kernels – End to end learning of the Fisher Kernel GMM parameters. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE; 2014:1402-1409. doi:10.1109/CVPR.2014.182
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2014 | Journal Article | IST-REx-ID: 2180 |
Bellet A, Habrard A, Morvant E, Sebban M. Learning a priori constrained weighted majority votes. Machine Learning. 2014;97(1-2):129-154. doi:10.1007/s10994-014-5462-z
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