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126 Publications
2018 | Published | Conference Paper | IST-REx-ID: 6011 | 
Kuzborskij, I., & Lampert, C. (2018). Data-dependent stability of stochastic gradient descent. In Proceedings of the 35 th International Conference on Machine Learning (Vol. 80, pp. 2815–2824). Stockholm, Sweden: ML Research Press.
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| arXiv
2018 | Research Data | IST-REx-ID: 5584 |
Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., & Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:98
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2018 | Published | Conference Paper | IST-REx-ID: 6589 |
Alistarh, D.-A., Hoefler, T., Johansson, M., Konstantinov, N. H., Khirirat, S., & Renggli, C. (2018). The convergence of sparsified gradient methods. In Advances in Neural Information Processing Systems 31 (Vol. Volume 2018, pp. 5973–5983). Montreal, Canada: Neural Information Processing Systems Foundation.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 750
Pielorz, J., Prandtstetter, M., Straub, M., & Lampert, C. (2017). Optimal geospatial volunteer allocation needs realistic distances. In 2017 IEEE International Conference on Big Data (pp. 3760–3763). Boston, MA, United States: IEEE. https://doi.org/10.1109/BigData.2017.8258375
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2017 | Published | Conference Paper | IST-REx-ID: 652
Der, R., & Martius, G. S. (2017). Dynamical self consistency leads to behavioral development and emergent social interactions in robots. Presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France: IEEE. https://doi.org/10.1109/DEVLRN.2016.7846789
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2017 | Published | Conference Paper | IST-REx-ID: 911 |
Royer, A., Kolesnikov, A., & Lampert, C. (2017). Probabilistic image colorization (p. 85.1-85.12). Presented at the BMVC: British Machine Vision Conference, London, United Kingdom: BMVA Press. https://doi.org/10.5244/c.31.85
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 1000 |
Kolesnikov, A., & Lampert, C. (2017). PixelCNN models with auxiliary variables for natural image modeling. In 34th International Conference on Machine Learning (Vol. 70, pp. 1905–1914). Sydney, Australia: JMLR.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 1108 |
Zimin, A., & Lampert, C. (2017). Learning theory for conditional risk minimization (Vol. 54, pp. 213–222). Presented at the AISTATS: Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States: ML Research Press.
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2017 | Published | Conference Paper | IST-REx-ID: 6841 |
Martius, G. S., & Lampert, C. (2017). Extrapolation and learning equations. In 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings. Toulon, France: International Conference on Learning Representations.
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2017 | Published | Journal Article | IST-REx-ID: 658 |
Der, Ralf, Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics 11 (MAR). 2017
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2017 | Published | Conference Paper | IST-REx-ID: 999 |
Pentina, A., & Lampert, C. (2017). Multi-task learning with labeled and unlabeled tasks (Vol. 70, pp. 2807–2816). Presented at the ICML: International Conference on Machine Learning, Sydney, Australia: ML Research Press.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 998 |
Rebuffi, S. A., Kolesnikov, A., Sperl, G., & Lampert, C. (2017). iCaRL: Incremental classifier and representation learning (Vol. 2017, pp. 5533–5542). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.587
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| arXiv
2016 | Published | Conference Paper | IST-REx-ID: 1707
Pielorz, J., & Lampert, C. (2016). Optimal geospatial allocation of volunteers for crisis management. Presented at the ICT-DM: Information and Communication Technologies for Disaster Management, Rennes, France: IEEE. https://doi.org/10.1109/ICT-DM.2015.7402041
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2016 | Published | Conference Paper | IST-REx-ID: 1214
Martius, G. S., Hostettler, R., Knoll, A., & Der, R. (2016). Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm (Vol. 2016–November). Presented at the IEEE RSJ International Conference on Intelligent Robots and Systems IROS , Daejeon, Korea: IEEE. https://doi.org/10.1109/IROS.2016.7759138
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2016 | Published | Conference Paper | IST-REx-ID: 8094 |
Martius, Georg S, Self-organized control of an tendon driven arm by differential extrinsic plasticity. 15th International Conference on the Synthesis and Simulation of Living Systems 28. 2016
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2016 | Published | Thesis | IST-REx-ID: 1126 |
Pentina, A. (2016). Theoretical foundations of multi-task lifelong learning. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:TH_776
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2016 | Published | Conference Paper | IST-REx-ID: 1102 |
Kolesnikov, A., & Lampert, C. (2016). Improving weakly-supervised object localization by micro-annotation. In Proceedings of the British Machine Vision Conference 2016 (Vol. 2016–September, p. 92.1-92.12). York, United Kingdom: BMVA Press. https://doi.org/10.5244/C.30.92
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2016 | Published | Conference Paper | IST-REx-ID: 1098 |
Pentina, A., & Urner, R. (2016). Lifelong learning with weighted majority votes (Vol. 29, pp. 3619–3627). Presented at the NIPS: Neural Information Processing Systems, Barcelona, Spain: Neural Information Processing Systems Foundation.
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2016 | Published | Conference Paper | IST-REx-ID: 1369 |
Kolesnikov, A., & Lampert, C. (2016). Seed, expand and constrain: Three principles for weakly-supervised image segmentation (Vol. 9908, pp. 695–711). Presented at the ECCV: European Conference on Computer Vision, Amsterdam, The Netherlands: Springer. https://doi.org/10.1007/978-3-319-46493-0_42
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| arXiv
2015 | Published | Thesis | IST-REx-ID: 1401 |
Sharmanska, V. (2015). Learning with attributes for object recognition: Parametric and non-parametrics views. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:1401
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