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114 Publications

2022 | Journal Article | IST-REx-ID: 12495 | OA
Iofinova EB, Konstantinov NH, Lampert C. FLEA: Provably robust fair multisource learning from unreliable training data. Transactions on Machine Learning Research. 2022.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2022 | Conference Paper | IST-REx-ID: 11839 | OA
Prach B, Lampert C. Almost-orthogonal layers for efficient general-purpose Lipschitz networks. In: Computer Vision – ECCV 2022. Vol 13681. Springer Nature; 2022:350-365. doi:10.1007/978-3-031-19803-8_21
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2022 | Conference Paper | IST-REx-ID: 10752
Lampert J, Lampert C. Overcoming rare-language discrimination in multi-lingual sentiment analysis. In: 2021 IEEE International Conference on Big Data. IEEE; 2022:5185-5192. doi:10.1109/bigdata52589.2021.9672003
View | DOI | WoS
 
2022 | Conference Paper | IST-REx-ID: 12161 | OA
Tomaszewska P, Lampert C. Lightweight conditional model extrapolation for streaming data under class-prior shift. In: 26th International Conference on Pattern Recognition. Vol 2022. Institute of Electrical and Electronics Engineers; 2022:2128-2134. doi:10.1109/icpr56361.2022.9956195
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Conference Paper | IST-REx-ID: 12299 | OA
Iofinova EB, Peste E-A, Kurtz M, Alistarh D-A. How well do sparse ImageNet models transfer? In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers; 2022:12256-12266. doi:10.1109/cvpr52688.2022.01195
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Journal Article | IST-REx-ID: 10802 | OA
Konstantinov NH, Lampert C. Fairness-aware PAC learning from corrupted data. Journal of Machine Learning Research. 2022;23:1-60.
[Published Version] View | Files available | arXiv
 
2022 | Conference Paper | IST-REx-ID: 13241 | OA
Konstantinov NH, Lampert C. On the impossibility of fairness-aware learning from corrupted data. In: Proceedings of Machine Learning Research. Vol 171. ML Research Press; 2022:59-83.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2022 | Thesis | IST-REx-ID: 10799 | OA
Konstantinov NH. Robustness and fairness in machine learning. 2022. doi:10.15479/at:ista:10799
[Published Version] View | Files available | DOI
 
2021 | Conference Paper | IST-REx-ID: 9210 | OA
Volhejn V, Lampert C. Does SGD implicitly optimize for smoothness? In: 42nd German Conference on Pattern Recognition. Vol 12544. LNCS. Springer; 2021:246-259. doi:10.1007/978-3-030-71278-5_18
[Submitted Version] View | Files available | DOI
 
2021 | Conference Paper | IST-REx-ID: 9416 | OA
Phuong M, Lampert C. 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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