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114 Publications
2023 | Conference Paper | IST-REx-ID: 14771 | 
Iofinova, E. B., Peste, E.-A., & Alistarh, D.-A. (2023). Bias in pruned vision models: In-depth analysis and countermeasures. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 24364–24373). Vancouver, BC, Canada: IEEE. https://doi.org/10.1109/cvpr52729.2023.02334
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| arXiv
2023 | Conference Paper | IST-REx-ID: 14921 |
Súkeník, P., Mondelli, M., & Lampert, C. (n.d.). Deep neural collapse is provably optimal for the deep unconstrained features model. In 37th Annual Conference on Neural Information Processing Systems. New Orleans, LA, United States.
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2023 | Preprint | IST-REx-ID: 15039 |
Prach, B., & Lampert, C. (n.d.). 1-Lipschitz neural networks are more expressive with N-activations. arXiv. https://doi.org/10.48550/ARXIV.2311.06103
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2022 | Preprint | IST-REx-ID: 12660 |
Scott, J. A., Yeo, M. X., & Lampert, C. (n.d.). Cross-client Label Propagation for transductive federated learning. arXiv. https://doi.org/10.48550/arXiv.2210.06434
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| arXiv
2022 | Preprint | IST-REx-ID: 12662 |
Súkeník, P., & Lampert, C. (n.d.). Generalization in Multi-objective machine learning. arXiv. https://doi.org/10.48550/arXiv.2208.13499
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2022 | Journal Article | IST-REx-ID: 12495 |
Iofinova, E. B., Konstantinov, N. H., & Lampert, C. (2022). FLEA: Provably robust fair multisource learning from unreliable training data. Transactions on Machine Learning Research. ML Research Press.
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2022 | Conference Paper | IST-REx-ID: 11839 |
Prach, B., & Lampert, C. (2022). Almost-orthogonal layers for efficient general-purpose Lipschitz networks. In Computer Vision – ECCV 2022 (Vol. 13681, pp. 350–365). Tel Aviv, Israel: Springer Nature. https://doi.org/10.1007/978-3-031-19803-8_21
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2022 | Conference Paper | IST-REx-ID: 10752
Lampert, J., & Lampert, C. (2022). Overcoming rare-language discrimination in multi-lingual sentiment analysis. In 2021 IEEE International Conference on Big Data (pp. 5185–5192). Orlando, FL, United States: IEEE. https://doi.org/10.1109/bigdata52589.2021.9672003
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2022 | Conference Paper | IST-REx-ID: 12161 |
Tomaszewska, P., & Lampert, C. (2022). Lightweight conditional model extrapolation for streaming data under class-prior shift. In 26th International Conference on Pattern Recognition (Vol. 2022, pp. 2128–2134). Montreal, Canada: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/icpr56361.2022.9956195
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2022 | Conference Paper | IST-REx-ID: 12299 |
Iofinova, E. B., Peste, E.-A., Kurtz, M., & Alistarh, D.-A. (2022). How well do sparse ImageNet models transfer? In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 12256–12266). New Orleans, LA, United States: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/cvpr52688.2022.01195
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| arXiv
2022 | Journal Article | IST-REx-ID: 10802 |
Konstantinov, N. H., & Lampert, C. (2022). Fairness-aware PAC learning from corrupted data. Journal of Machine Learning Research. ML Research Press.
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2022 | Conference Paper | IST-REx-ID: 13241 |
Konstantinov, N. H., & Lampert, C. (2022). On the impossibility of fairness-aware learning from corrupted data. In Proceedings of Machine Learning Research (Vol. 171, pp. 59–83). ML Research Press.
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2022 | Thesis | IST-REx-ID: 10799 |
Konstantinov, N. H. (2022). Robustness and fairness in machine learning. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10799
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2021 | Conference Paper | IST-REx-ID: 9210 |
Volhejn, V., & Lampert, C. (2021). Does SGD implicitly optimize for smoothness? In 42nd German Conference on Pattern Recognition (Vol. 12544, pp. 246–259). Tübingen, Germany: Springer. https://doi.org/10.1007/978-3-030-71278-5_18
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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. In 9th International Conference on Learning Representations. Virtual.
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2021 | Preprint | IST-REx-ID: 10803 |
Konstantinov, N. H., & Lampert, C. (n.d.). Fairness through regularization for learning to rank. arXiv. https://doi.org/10.48550/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. https://doi.org/10.15479/AT:ISTA:9418
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2021 | Book Chapter | IST-REx-ID: 14987
Lampert, C. (2021). Zero-Shot Learning. In K. Ikeuchi (Ed.), Computer Vision (2nd ed., pp. 1395–1397). Cham: Springer. https://doi.org/10.1007/978-3-030-63416-2_874
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2020 | Preprint | IST-REx-ID: 8063 |
Anciukevicius, T., Lampert, C., & Henderson, P. M. (n.d.). Object-centric image generation with factored depths, locations, and appearances. arXiv.
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2020 | Conference Paper | IST-REx-ID: 8188 |
Henderson, P. M., & Lampert, C. (2020). Unsupervised object-centric video generation and decomposition in 3D. In 34th Conference on Neural Information Processing Systems (Vol. 33, pp. 3106–3117). Vancouver, Canada: Curran Associates.
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