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77 Publications

2016 | Thesis | IST-REx-ID: 1126   OA
Pentina, A. (2016). Theoretical foundations of multi-task lifelong learning. IST Austria. https://doi.org/10.15479/AT:ISTA:TH_776
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2015 | Journal Article | IST-REx-ID: 1655   OA
Martius, G. S., & Olbrich, E. (2015). Quantifying emergent behavior of autonomous robots. Entropy, 17(10), 7266–7297. https://doi.org/10.3390/e17107266
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2015 | Conference Paper | IST-REx-ID: 1706   OA
Pentina, A., & Ben David, S. (2015). Multi-task and lifelong learning of kernels (Vol. 9355, pp. 194–208). Presented at the ALT: Algorithmic Learning Theory, Banff, AB, Canada: Springer. https://doi.org/10.1007/978-3-319-24486-0_13
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2015 | Conference Paper | IST-REx-ID: 1857   OA
Pentina, A., Sharmanska, V., & Lampert, C. (2015). Curriculum learning of multiple tasks (pp. 5492–5500). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States: IEEE. https://doi.org/10.1109/CVPR.2015.7299188
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2015 | Conference Paper | IST-REx-ID: 1858   OA
Lampert, C. (2015). Predicting the future behavior of a time-varying probability distribution (pp. 942–950). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States: IEEE. https://doi.org/10.1109/CVPR.2015.7298696
View | DOI | Download (ext.) | arXiv
 
2015 | Conference Paper | IST-REx-ID: 1860   OA
Royer, A., & Lampert, C. (2015). Classifier adaptation at prediction time (pp. 1401–1409). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, United States: IEEE. https://doi.org/10.1109/CVPR.2015.7298746
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2015 | Journal Article | IST-REx-ID: 1570   OA
Der, R., & Martius, G. S. (2015). Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS, 112(45), E6224–E6232. https://doi.org/10.1073/pnas.1508400112
View | DOI | Download (ext.) | PubMed | Europe PMC
 
2015 | Conference Paper | IST-REx-ID: 1859   OA
Shah, N., Kolmogorov, V., & Lampert, C. (2015). A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle (pp. 2737–2745). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA: IEEE. https://doi.org/10.1109/CVPR.2015.7298890
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2015 | Conference Paper | IST-REx-ID: 1425   OA
Pentina, A., & Lampert, C. (2015). Lifelong learning with non-i.i.d. tasks (Vol. 2015, pp. 1540–1548). Presented at the NIPS: Neural Information Processing Systems, Montreal, Canada: Neural Information Processing Systems.
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2015 | Thesis | IST-REx-ID: 1401
Sharmanska, V. (2015). Learning with attributes for object recognition: Parametric and non-parametrics views. IST Austria.
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2015 | Journal Article | IST-REx-ID: 1533
Xia, W., Domokos, C., Xiong, J., Cheong, L., & Yan, S. (2015). Segmentation over detection via optimal sparse reconstructions. IEEE Transactions on Circuits and Systems for Video Technology, 25(8), 1295–1308. https://doi.org/10.1109/TCSVT.2014.2379972
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2014 | Conference Paper | IST-REx-ID: 2171   OA
Kolesnikov, A., Guillaumin, M., Ferrari, V., & Lampert, C. (2014). Closed-form approximate CRF training for scalable image segmentation. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8691, pp. 550–565). Zurich, Switzerland: Springer. https://doi.org/10.1007/978-3-319-10578-9_36
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2014 | Conference Paper | IST-REx-ID: 2033   OA
Hernandez Lobato, D., Sharmanska, V., Kersting, K., Lampert, C., & Quadrianto, N. (2014). Mind the nuisance: Gaussian process classification using privileged noise. In Advances in Neural Information Processing Systems (Vol. 1, pp. 837–845). Montreal, Canada: Neural Information Processing Systems.
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2014 | Conference Paper | IST-REx-ID: 2057   OA
Morvant, E., Habrard, A., & Ayache, S. (2014). 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, pp. 153–162). Joensuu, Finland: Springer. https://doi.org/10.1007/978-3-662-44415-3_16
View | DOI | Download (ext.) | arXiv
 
2014 | Conference Paper | IST-REx-ID: 2172
Sydorov, V., Sakurada, M., & Lampert, C. (2014). 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 (pp. 1402–1409). Columbus, USA: IEEE. https://doi.org/10.1109/CVPR.2014.182
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2014 | Conference Paper | IST-REx-ID: 2189   OA
Morvant, E. (2014). Adaptation de domaine de vote de majorité par auto-étiquetage non itératif (Vol. 1, pp. 49–58). Presented at the CAP: Conférence Francophone sur l’Apprentissage Automatique (Machine Learning French Conference), Saint-Etienne, France: Elsevier.
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2014 | Conference Paper | IST-REx-ID: 2160   OA
Pentina, A., & Lampert, C. (2014). A PAC-Bayesian bound for Lifelong Learning. In E. Xing & T. Jebara (Eds.) (Vol. 32, pp. 991–999). Presented at the ICML: International Conference on Machine Learning, Beijing, China: Omnipress.
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2014 | Conference Paper | IST-REx-ID: 2173   OA
Khamis, S., & Lampert, C. (2014). CoConut: Co-classification with output space regularization. In Proceedings of the British Machine Vision Conference 2014. Nottingham, UK: BMVA Press.
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2014 | Journal Article | IST-REx-ID: 2180   OA
Bellet, A., Habrard, A., Morvant, E., & Sebban, M. (2014). Learning a priori constrained weighted majority votes. Machine Learning, 97(1–2), 129–154. https://doi.org/10.1007/s10994-014-5462-z
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2014 | Book Chapter | IST-REx-ID: 1829
Muelling, K., Kroemer, O., Lampert, C., & Schölkopf, B. (2014). Movement templates for learning of hitting and batting. In J. Kober & J. Peters (Eds.), Learning Motor Skills (Vol. 97, pp. 69–82). Springer. https://doi.org/10.1007/978-3-319-03194-1_3
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