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113 Publications

2023 | Conference Paper | IST-REx-ID: 13053 | OA
Peste, Elena-Alexandra, Adrian Vladu, Eldar Kurtic, Christoph Lampert, and Dan-Adrian Alistarh. “CrAM: A Compression-Aware Minimizer.” In 11th International Conference on Learning Representations , n.d.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2023 | Thesis | IST-REx-ID: 13074 | OA
Peste, Elena-Alexandra. “Efficiency and Generalization of Sparse Neural Networks.” Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/at:ista:13074.
[Published Version] View | Files available | DOI
 
2023 | Journal Article | IST-REx-ID: 14320 | OA
Henderson, Paul M, Areg Ghazaryan, Alexander A. Zibrov, Andrea F. Young, and Maksym Serbyn. “Deep Learning Extraction of Band Structure Parameters from Density of States: A Case Study on Trilayer Graphene.” Physical Review B. American Physical Society, 2023. https://doi.org/10.1103/physrevb.108.125411.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
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.” In International Workshop on Reproducible Research in Pattern Recognition, 14068:67–73. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-40773-4_6.
View | DOI
 
2023 | Journal Article | IST-REx-ID: 14446 | OA
Jakubík, Jozef, Mary Phuong, Martina Chvosteková, and Anna Krakovská. “Against the Flow of Time with Multi-Output Models.” Measurement Science Review. Sciendo, 2023. https://doi.org/10.2478/msr-2023-0023.
[Published Version] View | Files available | DOI
 
2023 | Conference Paper | IST-REx-ID: 14771 | OA
Iofinova, Eugenia B, Elena-Alexandra Peste, and Dan-Adrian Alistarh. “Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures.” In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 24364–73. IEEE, 2023. https://doi.org/10.1109/cvpr52729.2023.02334.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14921 | OA
Súkeník, Peter, Marco Mondelli, and Christoph Lampert. “Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model.” In 37th Annual Conference on Neural Information Processing Systems, n.d.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2023 | Preprint | IST-REx-ID: 15039 | OA
Prach, Bernd, and Christoph Lampert. “1-Lipschitz Neural Networks Are More Expressive with N-Activations.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2311.06103.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2022 | Preprint | IST-REx-ID: 12660 | OA
Scott, Jonathan A, Michelle X Yeo, and Christoph Lampert. “Cross-Client Label Propagation for Transductive Federated Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2210.06434.
[Preprint] View | Files available | DOI | arXiv
 
2022 | Preprint | IST-REx-ID: 12662 | OA
Súkeník, Peter, and Christoph Lampert. “Generalization in Multi-Objective Machine Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2208.13499.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2022 | Journal Article | IST-REx-ID: 12495 | OA
Iofinova, Eugenia B, Nikola H Konstantinov, and Christoph Lampert. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” Transactions on Machine Learning Research. ML Research Press, 2022.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2022 | Conference Paper | IST-REx-ID: 11839 | OA
Prach, Bernd, and Christoph Lampert. “Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks.” In Computer Vision – ECCV 2022, 13681:350–65. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-19803-8_21.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2022 | Conference Paper | IST-REx-ID: 10752
Lampert, Jasmin, and Christoph Lampert. “Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis.” In 2021 IEEE International Conference on Big Data, 5185–92. IEEE, 2022. https://doi.org/10.1109/bigdata52589.2021.9672003.
View | DOI | WoS
 
2022 | Conference Paper | IST-REx-ID: 12161 | OA
Tomaszewska, Paulina, and Christoph Lampert. “Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift.” In 26th International Conference on Pattern Recognition, 2022:2128–34. Institute of Electrical and Electronics Engineers, 2022. https://doi.org/10.1109/icpr56361.2022.9956195.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Conference Paper | IST-REx-ID: 12299 | OA
Iofinova, Eugenia B, Elena-Alexandra Peste, Mark Kurtz, and Dan-Adrian Alistarh. “How Well Do Sparse ImageNet Models Transfer?” In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 12256–66. Institute of Electrical and Electronics Engineers, 2022. https://doi.org/10.1109/cvpr52688.2022.01195.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Journal Article | IST-REx-ID: 10802 | OA
Konstantinov, Nikola H, and Christoph Lampert. “Fairness-Aware PAC Learning from Corrupted Data.” Journal of Machine Learning Research. ML Research Press, 2022.
[Published Version] View | Files available | arXiv
 
2022 | Conference Paper | IST-REx-ID: 13241 | OA
Konstantinov, Nikola H, and Christoph Lampert. “On the Impossibility of Fairness-Aware Learning from Corrupted Data.” In Proceedings of Machine Learning Research, 171:59–83. ML Research Press, 2022.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2022 | Thesis | IST-REx-ID: 10799 | OA
Konstantinov, Nikola H. “Robustness and Fairness in Machine Learning.” Institute of Science and Technology Austria, 2022. https://doi.org/10.15479/at:ista:10799.
[Published Version] View | Files available | DOI
 
2021 | Conference Paper | IST-REx-ID: 9210 | OA
Volhejn, Vaclav, and Christoph Lampert. “Does SGD Implicitly Optimize for Smoothness?” In 42nd German Conference on Pattern Recognition, 12544:246–59. LNCS. Springer, 2021. https://doi.org/10.1007/978-3-030-71278-5_18.
[Submitted Version] View | Files available | DOI
 
2021 | Conference Paper | IST-REx-ID: 9416 | OA
Phuong, Mary, and Christoph Lampert. “The Inductive Bias of ReLU Networks on Orthogonally Separable Data.” In 9th International Conference on Learning Representations, 2021.
[Published Version] View | Files available | Download Published Version (ext.)
 

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