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114 Publications
2020 | Conference Paper | IST-REx-ID: 8724 | 
Konstantinov, Nikola H, Elias Frantar, Dan-Adrian Alistarh, and Christoph Lampert. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.” In Proceedings of the 37th International Conference on Machine Learning, 119:5416–25. ML Research Press, 2020.
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| arXiv
2020 | Thesis | IST-REx-ID: 8390 |
Royer, Amélie. “Leveraging Structure in Computer Vision Tasks for Flexible Deep Learning Models.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8390.
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2020 | Conference Paper | IST-REx-ID: 8186 |
Henderson, Paul M, Vagia Tsiminaki, and Christoph Lampert. “Leveraging 2D Data to Learn Textured 3D Mesh Generation.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 7498–7507. IEEE, 2020. https://doi.org/10.1109/CVPR42600.2020.00752.
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2020 | Journal Article | IST-REx-ID: 6944 |
Sun, Rémy, and Christoph Lampert. “KS(Conf): A Light-Weight Test If a Multiclass Classifier Operates Outside of Its Specifications.” International Journal of Computer Vision. Springer Nature, 2020. https://doi.org/10.1007/s11263-019-01232-x.
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2019 | Book (Editor) | IST-REx-ID: 7171
Kersting, Kristian, Christoph Lampert, and Constantin Rothkopf, eds. Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt. 1st ed. Wiesbaden: Springer Nature, 2019. https://doi.org/10.1007/978-3-658-26763-6.
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2019 | Conference Paper | IST-REx-ID: 6942 |
Ashok, Pranav, Tomáš Brázdil, Krishnendu Chatterjee, Jan Křetínský, Christoph Lampert, and Viktor Toman. “Strategy Representation by Decision Trees with Linear Classifiers.” In 16th International Conference on Quantitative Evaluation of Systems, 11785:109–28. Springer Nature, 2019. https://doi.org/10.1007/978-3-030-30281-8_7.
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| arXiv
2019 | Journal Article | IST-REx-ID: 6554 |
Xian, Yongqin, Christoph Lampert, Bernt Schiele, and Zeynep Akata. “Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly.” IEEE Transactions on Pattern Analysis and Machine Intelligence. Institute of Electrical and Electronics Engineers (IEEE), 2019. https://doi.org/10.1109/tpami.2018.2857768.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 7479 |
Phuong, Mary, and Christoph Lampert. “Distillation-Based Training for Multi-Exit Architectures.” In IEEE International Conference on Computer Vision, 2019–October:1355–64. IEEE, 2019. https://doi.org/10.1109/ICCV.2019.00144.
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2019 | Conference Paper | IST-REx-ID: 7640 |
Kolesnikov, Alexander, Alina Kuznetsova, Christoph Lampert, and Vittorio Ferrari. “Detecting Visual Relationships Using Box Attention.” In Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE, 2019. https://doi.org/10.1109/ICCVW.2019.00217.
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2019 | Conference Paper | IST-REx-ID: 6569 |
Phuong, Mary, and Christoph Lampert. “Towards Understanding Knowledge Distillation.” In Proceedings of the 36th International Conference on Machine Learning, 97:5142–51. ML Research Press, 2019.
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2019 | Conference Paper | IST-REx-ID: 6590 |
Konstantinov, Nikola H, and Christoph Lampert. “Robust Learning from Untrusted Sources.” In Proceedings of the 36th International Conference on Machine Learning, 97:3488–98. ML Research Press, 2019.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 6482 |
Sun, Rémy, and Christoph Lampert. “KS(Conf): A Light-Weight Test If a ConvNet Operates Outside of Its Specifications,” 11269:244–59. Springer Nature, 2019. https://doi.org/10.1007/978-3-030-12939-2_18.
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2018 | Thesis | IST-REx-ID: 68 |
Zimin, Alexander. “Learning from Dependent Data.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:TH1048.
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2018 | Thesis | IST-REx-ID: 197 |
Kolesnikov, Alexander. “Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:th_1021.
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2018 | Journal Article | IST-REx-ID: 563 |
Ringbauer, Harald, Alexander Kolesnikov, David Field, and Nicholas H Barton. “Estimating Barriers to Gene Flow from Distorted Isolation-by-Distance Patterns.” Genetics. Genetics Society of America, 2018. https://doi.org/10.1534/genetics.117.300638.
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2018 | Journal Article | IST-REx-ID: 321 |
Darrell, Trevor, Christoph Lampert, Nico Sebe, Ying Wu, and Yan Yan. “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, 2018. https://doi.org/10.1109/TPAMI.2018.2804998.
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2018 | Conference Paper | IST-REx-ID: 10882 |
Uijlings, Jasper, Ksenia Konyushkova, Christoph Lampert, and Vittorio Ferrari. “Learning Intelligent Dialogs for Bounding Box Annotation.” In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 9175–84. IEEE, 2018. https://doi.org/10.1109/cvpr.2018.00956.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 6012 |
Sahoo, Subham, Christoph Lampert, and Georg S Martius. “Learning Equations for Extrapolation and Control.” In Proceedings of the 35th International Conference on Machine Learning, 80:4442–50. ML Research Press, 2018.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 6011 |
Kuzborskij, Ilja, and Christoph Lampert. “Data-Dependent Stability of Stochastic Gradient Descent.” In Proceedings of the 35 Th International Conference on Machine Learning, 80:2815–24. ML Research Press, 2018.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 6589 |
Alistarh, Dan-Adrian, Torsten Hoefler, Mikael Johansson, Nikola H Konstantinov, Sarit Khirirat, and Cedric Renggli. “The Convergence of Sparsified Gradient Methods.” In Advances in Neural Information Processing Systems 31, Volume 2018:5973–83. Neural Information Processing Systems Foundation, 2018.
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