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114 Publications

2019 | Conference Paper | IST-REx-ID: 6590 | OA
Konstantinov, N. H., & Lampert, C. (2019). Robust learning from untrusted sources. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 3488–3498). Long Beach, CA, USA: ML Research Press.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 6482 | OA
Sun, R., & Lampert, C. (2019). KS(conf): A light-weight test if a ConvNet operates outside of Its specifications (Vol. 11269, pp. 244–259). Presented at the GCPR: Conference on Pattern Recognition, Stuttgart, Germany: Springer Nature. https://doi.org/10.1007/978-3-030-12939-2_18
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2018 | Thesis | IST-REx-ID: 68 | OA
Zimin, A. (2018). Learning from dependent data. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:TH1048
[Published Version] View | Files available | DOI
 
2018 | Thesis | IST-REx-ID: 197 | OA
Kolesnikov, A. (2018). Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_1021
[Published Version] View | Files available | DOI
 
2018 | Journal Article | IST-REx-ID: 563 | OA
Ringbauer, H., Kolesnikov, A., Field, D., & Barton, N. H. (2018). Estimating barriers to gene flow from distorted isolation-by-distance patterns. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.117.300638
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS
 
2018 | Journal Article | IST-REx-ID: 321 | OA
Darrell, T., Lampert, C., Sebe, N., Wu, Y., & Yan, Y. (2018). Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2018.2804998
[Published Version] View | Files available | DOI | WoS
 
2018 | Conference Paper | IST-REx-ID: 10882 | OA
Uijlings, J., Konyushkova, K., Lampert, C., & Ferrari, V. (2018). Learning intelligent dialogs for bounding box annotation. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 9175–9184). Salt Lake City, UT, United States: IEEE. https://doi.org/10.1109/cvpr.2018.00956
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2018 | Conference Paper | IST-REx-ID: 6012 | OA
Sahoo, S., Lampert, C., & Martius, G. S. (2018). Learning equations for extrapolation and control. In Proceedings of the 35th International Conference on Machine Learning (Vol. 80, pp. 4442–4450). Stockholm, Sweden: ML Research Press.
[Preprint] View | Files available | Download Preprint (ext.) | WoS | arXiv
 
2018 | Conference Paper | IST-REx-ID: 6011 | OA
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.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 
2018 | Conference Paper | IST-REx-ID: 6589 | OA
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.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 

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