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127 Publications

2023 | Published | Conference Paper | IST-REx-ID: 14771 | OA
E. B. Iofinova, A. Krumes, and D.-A. Alistarh, “Bias in pruned vision models: In-depth analysis and countermeasures,” in 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, BC, Canada, 2023, pp. 24364–24373.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2023 | Draft | Preprint | IST-REx-ID: 15039 | OA
B. Prach and C. Lampert, “1-Lipschitz neural networks are more expressive with N-activations,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 13241 | OA
N. H. Konstantinov and C. Lampert, “On the impossibility of fairness-aware learning from corrupted data,” in Proceedings of Machine Learning Research, 2022, vol. 171, pp. 59–83.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 12161 | OA
P. Tomaszewska and C. Lampert, “Lightweight conditional model extrapolation for streaming data under class-prior shift,” in 26th International Conference on Pattern Recognition, Montreal, Canada, 2022, vol. 2022, pp. 2128–2134.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 10752
J. Lampert and C. Lampert, “Overcoming rare-language discrimination in multi-lingual sentiment analysis,” in 2021 IEEE International Conference on Big Data, Orlando, FL, United States, 2022, pp. 5185–5192.
View | DOI | WoS
 
2022 | Published | Journal Article | IST-REx-ID: 10802 | OA
N. H. Konstantinov and C. Lampert, “Fairness-aware PAC learning from corrupted data,” Journal of Machine Learning Research, vol. 23. ML Research Press, pp. 1–60, 2022.
[Published Version] View | Files available | arXiv
 
2022 | Published | Journal Article | IST-REx-ID: 12495 | OA
E. B. Iofinova, N. H. Konstantinov, and C. 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 | Published | Conference Paper | IST-REx-ID: 12299 | OA
E. B. Iofinova, A. Krumes, M. Kurtz, and D.-A. Alistarh, “How well do sparse ImageNet models transfer?,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, United States, 2022, pp. 12256–12266.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 11839 | OA
B. Prach and C. Lampert, “Almost-orthogonal layers for efficient general-purpose Lipschitz networks,” in Computer Vision – ECCV 2022, Tel Aviv, Israel, 2022, vol. 13681, pp. 350–365.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2022 | Published | Thesis | IST-REx-ID: 10799 | OA
N. H. Konstantinov, “Robustness and fairness in machine learning,” Institute of Science and Technology Austria, 2022.
[Published Version] View | Files available | DOI
 
2021 | Published | Book Chapter | IST-REx-ID: 14987
C. Lampert, “Zero-Shot Learning,” in Computer Vision, 2nd ed., K. Ikeuchi, Ed. Cham: Springer, 2021, pp. 1395–1397.
View | DOI
 
2021 | Published | Conference Paper | IST-REx-ID: 9210 | OA
V. Volhejn and C. Lampert, “Does SGD implicitly optimize for smoothness?,” in 42nd German Conference on Pattern Recognition, Tübingen, Germany, 2021, vol. 12544, pp. 246–259.
[Submitted Version] View | Files available | DOI
 
2021 | Draft | Preprint | IST-REx-ID: 10803 | OA
N. H. Konstantinov and C. Lampert, “Fairness through regularization for learning to rank,” arXiv. .
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 9416 | OA
M. Phuong and C. Lampert, “The inductive bias of ReLU networks on orthogonally separable data,” in 9th International Conference on Learning Representations, Virtual, 2021.
[Published Version] View | Files available | Download Published Version (ext.)
 
2021 | Published | Thesis | IST-REx-ID: 9418 | OA
M. Phuong, “Underspecification in deep learning,” Institute of Science and Technology Austria, 2021.
[Published Version] View | Files available | DOI
 
2020 | Published | Conference Paper | IST-REx-ID: 8186 | OA
P. M. Henderson, V. Tsiminaki, and C. Lampert, “Leveraging 2D data to learn textured 3D mesh generation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Virtual, 2020, pp. 7498–7507.
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | arXiv
 
2020 | Submitted | Preprint | IST-REx-ID: 8063 | OA
T. Anciukevicius, C. Lampert, and P. M. Henderson, “Object-centric image generation with factored depths, locations, and appearances,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2020 | Published | Journal Article | IST-REx-ID: 6952 | OA
P. M. Henderson and V. Ferrari, “Learning single-image 3D reconstruction by generative modelling of shape, pose and shading,” International Journal of Computer Vision, vol. 128. Springer Nature, pp. 835–854, 2020.
[Published Version] View | Files available | DOI | WoS | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 7936 | OA
A. Royer and C. Lampert, “Localizing grouped instances for efficient detection in low-resource scenarios,” in IEEE Winter Conference on Applications of Computer Vision, Snowmass Village, CO, United States, 2020.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 7937 | OA
A. Royer and C. Lampert, “A flexible selection scheme for minimum-effort transfer learning,” in 2020 IEEE Winter Conference on Applications of Computer Vision, Snowmass Village, CO, United States, 2020.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

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