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113 Publications
2023 | Conference Paper | IST-REx-ID: 13053 | 
Peste, Elena-Alexandra, et al. “CrAM: A Compression-Aware Minimizer.” 11th International Conference on Learning Representations .
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| arXiv
2023 | Thesis | IST-REx-ID: 13074 |
Peste, Elena-Alexandra. Efficiency and Generalization of Sparse Neural Networks. Institute of Science and Technology Austria, 2023, doi:10.15479/at:ista:13074.
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2023 | Journal Article | IST-REx-ID: 14320 |
Henderson, Paul M., et al. “Deep Learning Extraction of Band Structure Parameters from Density of States: A Case Study on Trilayer Graphene.” Physical Review B, vol. 108, no. 12, 125411, American Physical Society, 2023, doi:10.1103/physrevb.108.125411.
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2023 | Conference Paper | IST-REx-ID: 14410
Tomaszewska, Paulina, and Christoph Lampert. “On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) under Class-Prior Shift.” International Workshop on Reproducible Research in Pattern Recognition, vol. 14068, Springer Nature, 2023, pp. 67–73, doi:10.1007/978-3-031-40773-4_6.
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2023 | Journal Article | IST-REx-ID: 14446 |
Jakubík, Jozef, et al. “Against the Flow of Time with Multi-Output Models.” Measurement Science Review, vol. 23, no. 4, Sciendo, 2023, pp. 175–83, doi:10.2478/msr-2023-0023.
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2023 | Conference Paper | IST-REx-ID: 14771 |
Iofinova, Eugenia B., et al. “Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures.” 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–73, doi:10.1109/cvpr52729.2023.02334.
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| arXiv
2023 | Conference Paper | IST-REx-ID: 14921 |
Súkeník, Peter, et al. “Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model.” 37th Annual Conference on Neural Information Processing Systems.
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| arXiv
2023 | Preprint | IST-REx-ID: 15039 |
Prach, Bernd, and Christoph Lampert. “1-Lipschitz Neural Networks Are More Expressive with N-Activations.” ArXiv, 2311.06103, doi:10.48550/ARXIV.2311.06103.
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2022 | Preprint | IST-REx-ID: 12660 |
Scott, Jonathan A., et al. “Cross-Client Label Propagation for Transductive Federated Learning.” ArXiv, 2210.06434, doi:10.48550/arXiv.2210.06434.
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| arXiv
2022 | Preprint | IST-REx-ID: 12662 |
Súkeník, Peter, and Christoph Lampert. “Generalization in Multi-Objective Machine Learning.” ArXiv, 2208.13499, doi:10.48550/arXiv.2208.13499.
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2022 | Journal Article | IST-REx-ID: 12495 |
Iofinova, Eugenia B., et al. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” Transactions on Machine Learning Research, ML Research Press, 2022.
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| arXiv
2022 | Conference Paper | IST-REx-ID: 11839 |
Prach, Bernd, and Christoph Lampert. “Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks.” Computer Vision – ECCV 2022, vol. 13681, Springer Nature, 2022, pp. 350–65, doi:10.1007/978-3-031-19803-8_21.
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2022 | Conference Paper | IST-REx-ID: 10752
Lampert, Jasmin, and Christoph Lampert. “Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis.” 2021 IEEE International Conference on Big Data, IEEE, 2022, pp. 5185–92, doi:10.1109/bigdata52589.2021.9672003.
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2022 | Conference Paper | IST-REx-ID: 12161 |
Tomaszewska, Paulina, and Christoph Lampert. “Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift.” 26th International Conference on Pattern Recognition, vol. 2022, Institute of Electrical and Electronics Engineers, 2022, pp. 2128–34, doi:10.1109/icpr56361.2022.9956195.
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2022 | Conference Paper | IST-REx-ID: 12299 |
Iofinova, Eugenia B., et al. “How Well Do Sparse ImageNet Models Transfer?” 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–66, doi:10.1109/cvpr52688.2022.01195.
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| arXiv
2022 | Journal Article | IST-REx-ID: 10802 |
Konstantinov, Nikola H., and Christoph Lampert. “Fairness-Aware PAC Learning from Corrupted Data.” Journal of Machine Learning Research, vol. 23, ML Research Press, 2022, pp. 1–60.
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2022 | Conference Paper | IST-REx-ID: 13241 |
Konstantinov, Nikola H., and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” Proceedings of Machine Learning Research, vol. 171, ML Research Press, 2022, pp. 59–83.
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| arXiv
2022 | Thesis | IST-REx-ID: 10799 |
Konstantinov, Nikola H. Robustness and Fairness in Machine Learning. Institute of Science and Technology Austria, 2022, doi:10.15479/at:ista:10799.
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2021 | Conference Paper | IST-REx-ID: 9210 |
Volhejn, Vaclav, and Christoph Lampert. “Does SGD Implicitly Optimize for Smoothness?” 42nd German Conference on Pattern Recognition, vol. 12544, Springer, 2021, pp. 246–59, doi:10.1007/978-3-030-71278-5_18.
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2021 | Conference Paper | IST-REx-ID: 9416 |
Phuong, Mary, and Christoph Lampert. “The Inductive Bias of ReLU Networks on Orthogonally Separable Data.” 9th International Conference on Learning Representations, 2021.
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