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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. Proceedings of the 35 th International Conference on Machine Learning. ICML: International Conference on Machine Learning vol. 80, 2815–2824.
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| arXiv
2018 | Research Data | IST-REx-ID: 5584 |
Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. 2018. Nonlinear decoding of a complex movie from the mammalian retina, Institute of Science and Technology Austria, 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 NH, Khirirat S, Renggli C. 2018. The convergence of sparsified gradient methods. Advances in Neural Information Processing Systems 31. NeurIPS: Conference on Neural Information Processing Systems vol. Volume 2018, 5973–5983.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 911 |
Royer A, Kolesnikov A, Lampert C. 2017. Probabilistic image colorization. BMVC: British Machine Vision Conference, 85.1-85.12.
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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. 34th International Conference on Machine Learning. ICML: International Conference on Machine Learning vol. 70, 1905–1914.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 1108 |
Zimin A, Lampert C. 2017. Learning theory for conditional risk minimization. AISTATS: Artificial Intelligence and Statistics, PMLR, vol. 54, 213–222.
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2017 | Published | Conference Paper | IST-REx-ID: 6841 |
Martius GS, Lampert C. 2017. Extrapolation and learning equations. 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings. ICLR: International Conference on Learning Representations.
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| arXiv
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. ICML: International Conference on Machine Learning, PMLR, vol. 70, 2807–2816.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 998 |
Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. 2017. iCaRL: Incremental classifier and representation learning. CVPR: Computer Vision and Pattern Recognition vol. 2017, 5533–5542.
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| arXiv
2016 | Published | Conference Paper | IST-REx-ID: 1214
Martius GS, Hostettler R, Knoll A, Der R. 2016. Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm. IEEE RSJ International Conference on Intelligent Robots and Systems IROS vol. 2016–November, 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.
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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. Proceedings of the British Machine Vision Conference 2016. BMVC: British Machine Vision Conference vol. 2016–September, 92.1-92.12.
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2016 | Published | Conference Paper | IST-REx-ID: 1098 |
Pentina A, Urner R. 2016. Lifelong learning with weighted majority votes. NIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 29, 3619–3627.
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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. ECCV: European Conference on Computer Vision, LNCS, vol. 9908, 695–711.
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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.
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