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114 Publications
2022 | Journal Article | IST-REx-ID: 12495 | 
Iofinova EB, Konstantinov NH, Lampert C. 2022. FLEA: Provably robust fair multisource learning from unreliable training data. Transactions on Machine Learning Research.
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| arXiv
2022 | Conference Paper | IST-REx-ID: 11839 |
Prach B, Lampert C. 2022. Almost-orthogonal layers for efficient general-purpose Lipschitz networks. Computer Vision – ECCV 2022. ECCV: European Conference on Computer Vision, LNCS, vol. 13681, 350–365.
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| arXiv
2022 | Conference Paper | IST-REx-ID: 12161 |
Tomaszewska P, Lampert C. 2022. Lightweight conditional model extrapolation for streaming data under class-prior shift. 26th International Conference on Pattern Recognition. ICPR: International Conference on Pattern Recognition vol. 2022, 2128–2134.
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| arXiv
2022 | Conference Paper | IST-REx-ID: 12299 |
Iofinova EB, Peste E-A, Kurtz M, Alistarh D-A. 2022. How well do sparse ImageNet models transfer? 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR: Computer Vision and Pattern Recognition, 12256–12266.
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2022 | Journal Article | IST-REx-ID: 10802 |
Konstantinov NH, Lampert C. 2022. Fairness-aware PAC learning from corrupted data. Journal of Machine Learning Research. 23, 1–60.
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2022 | Conference Paper | IST-REx-ID: 13241 |
Konstantinov NH, Lampert C. 2022. On the impossibility of fairness-aware learning from corrupted data. Proceedings of Machine Learning Research. vol. 171, 59–83.
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| arXiv
2022 | Thesis | IST-REx-ID: 10799 |
Konstantinov NH. 2022. Robustness and fairness in machine learning. Institute of Science and Technology Austria.
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2021 | Conference Paper | IST-REx-ID: 9210 |
Volhejn V, Lampert C. 2021. Does SGD implicitly optimize for smoothness? 42nd German Conference on Pattern Recognition. DAGM GCPR: German Conference on Pattern Recognition LNCS vol. 12544, 246–259.
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2021 | Conference Paper | IST-REx-ID: 9416 |
Phuong M, Lampert C. 2021. The inductive bias of ReLU networks on orthogonally separable data. 9th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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2021 | Preprint | IST-REx-ID: 10803 |
Konstantinov NH, Lampert C. Fairness through regularization for learning to rank. arXiv, 2102.05996.
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2021 | Thesis | IST-REx-ID: 9418 |
Phuong M. 2021. Underspecification in deep learning. Institute of Science and Technology Austria.
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2020 | Preprint | IST-REx-ID: 8063 |
Anciukevicius T, Lampert C, Henderson PM. Object-centric image generation with factored depths, locations, and appearances. arXiv, 2004.00642.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 8188 |
Henderson PM, Lampert C. 2020. Unsupervised object-centric video generation and decomposition in 3D. 34th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 33, 3106–3117.
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| arXiv
2020 | Journal Article | IST-REx-ID: 6952 |
Henderson PM, Ferrari V. 2020. Learning single-image 3D reconstruction by generative modelling of shape, pose and shading. International Journal of Computer Vision. 128, 835–854.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 7936 |
Royer A, Lampert C. 2020. Localizing grouped instances for efficient detection in low-resource scenarios. IEEE Winter Conference on Applications of Computer Vision. WACV: Winter Conference on Applications of Computer Vision, 1716–1725.
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2020 | Conference Paper | IST-REx-ID: 7937 |
Royer A, Lampert C. 2020. A flexible selection scheme for minimum-effort transfer learning. 2020 IEEE Winter Conference on Applications of Computer Vision. WACV: Winter Conference on Applications of Computer Vision, 2180–2189.
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| arXiv
2020 | Book Chapter | IST-REx-ID: 8092 |
Royer A, Bousmalis K, Gouws S, Bertsch F, Mosseri I, Cole F, Murphy K. 2020.XGAN: Unsupervised image-to-image translation for many-to-many mappings. In: Domain Adaptation for Visual Understanding. , 33–49.
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2020 | Conference Paper | IST-REx-ID: 7481 |
Phuong M, Lampert C. 2020. Functional vs. parametric equivalence of ReLU networks. 8th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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