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114 Publications


2023 | Conference Paper | IST-REx-ID: 13053 | OA
CrAM: A Compression-Aware Minimizer
E.-A. Peste, A. Vladu, E. Kurtic, C. Lampert, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , n.d.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2023 | Thesis | IST-REx-ID: 13074 | OA
Efficiency and generalization of sparse neural networks
E.-A. Peste, Efficiency and Generalization of Sparse Neural Networks, Institute of Science and Technology Austria, 2023.
[Published Version] View | Files available | DOI
 

2023 | Journal Article | IST-REx-ID: 14320 | OA
Deep learning extraction of band structure parameters from density of states: A case study on trilayer graphene
P.M. Henderson, A. Ghazaryan, A.A. Zibrov, A.F. Young, M. Serbyn, Physical Review B 108 (2023).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14410
On the implementation of baselines and lightweight conditional model extrapolation (LIMES) under class-prior shift
P. Tomaszewska, C. Lampert, in:, International Workshop on Reproducible Research in Pattern Recognition, Springer Nature, 2023, pp. 67–73.
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2023 | Journal Article | IST-REx-ID: 14446 | OA
Against the flow of time with multi-output models
J. Jakubík, M. Phuong, M. Chvosteková, A. Krakovská, Measurement Science Review 23 (2023) 175–183.
[Published Version] View | Files available | DOI
 

2023 | Conference Paper | IST-REx-ID: 14771 | OA
Bias in pruned vision models: In-depth analysis and countermeasures
E.B. Iofinova, E.-A. Peste, D.-A. Alistarh, in:, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–24373.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14921 | OA
Deep neural collapse is provably optimal for the deep unconstrained features model
P. Súkeník, M. Mondelli, C. Lampert, in:, 37th Annual Conference on Neural Information Processing Systems, n.d.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 15039 | OA [Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 | Preprint | IST-REx-ID: 12660 | OA
Cross-client Label Propagation for transductive federated learning
J.A. Scott, M.X. Yeo, C. Lampert, ArXiv (n.d.).
[Preprint] View | Files available | DOI | arXiv
 

2022 | Preprint | IST-REx-ID: 12662 | OA
Generalization in Multi-objective machine learning
P. Súkeník, C. Lampert, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 | Journal Article | IST-REx-ID: 12495 | OA
FLEA: Provably robust fair multisource learning from unreliable training data
E.B. Iofinova, N.H. Konstantinov, C. Lampert, Transactions on Machine Learning Research (2022).
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 11839 | OA
Almost-orthogonal layers for efficient general-purpose Lipschitz networks
B. Prach, C. Lampert, in:, Computer Vision – ECCV 2022, Springer Nature, 2022, pp. 350–365.
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2022 | Conference Paper | IST-REx-ID: 10752
Overcoming rare-language discrimination in multi-lingual sentiment analysis
J. Lampert, C. Lampert, in:, 2021 IEEE International Conference on Big Data, IEEE, 2022, pp. 5185–5192.
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2022 | Conference Paper | IST-REx-ID: 12161 | OA
Lightweight conditional model extrapolation for streaming data under class-prior shift
P. Tomaszewska, C. Lampert, in:, 26th International Conference on Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 2128–2134.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2022 | Conference Paper | IST-REx-ID: 12299 | OA
How well do sparse ImageNet models transfer?
E.B. Iofinova, E.-A. Peste, M. Kurtz, D.-A. Alistarh, in:, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–12266.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2022 | Journal Article | IST-REx-ID: 10802 | OA
Fairness-aware PAC learning from corrupted data
N.H. Konstantinov, C. Lampert, Journal of Machine Learning Research 23 (2022) 1–60.
[Published Version] View | Files available | arXiv
 

2022 | Conference Paper | IST-REx-ID: 13241 | OA
On the impossibility of fairness-aware learning from corrupted data
N.H. Konstantinov, C. Lampert, in:, Proceedings of Machine Learning Research, ML Research Press, 2022, pp. 59–83.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2022 | Thesis | IST-REx-ID: 10799 | OA
Robustness and fairness in machine learning
N.H. Konstantinov, Robustness and Fairness in Machine Learning, Institute of Science and Technology Austria, 2022.
[Published Version] View | Files available | DOI
 

2021 | Conference Paper | IST-REx-ID: 9210 | OA
Does SGD implicitly optimize for smoothness?
V. Volhejn, C. Lampert, in:, 42nd German Conference on Pattern Recognition, Springer, 2021, pp. 246–259.
[Submitted Version] View | Files available | DOI
 

2021 | Conference Paper | IST-REx-ID: 9416 | OA
The inductive bias of ReLU networks on orthogonally separable data
M. Phuong, C. Lampert, in:, 9th International Conference on Learning Representations, 2021.
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2021 | Preprint | IST-REx-ID: 10803 | OA
Fairness through regularization for learning to rank
N.H. Konstantinov, C. Lampert, ArXiv (n.d.).
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Thesis | IST-REx-ID: 9418 | OA
Underspecification in deep learning
M. Phuong, Underspecification in Deep Learning, Institute of Science and Technology Austria, 2021.
[Published Version] View | Files available | DOI
 

2021 | Book Chapter | IST-REx-ID: 14987
Zero-Shot Learning
C. Lampert, in:, K. Ikeuchi (Ed.), Computer Vision, 2nd ed., Springer, Cham, 2021, pp. 1395–1397.
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2020 | Preprint | IST-REx-ID: 8063 | OA
Object-centric image generation with factored depths, locations, and appearances
T. Anciukevicius, C. Lampert, P.M. Henderson, ArXiv (n.d.).
[Preprint] View | Download Preprint (ext.) | arXiv
 

2020 | Conference Paper | IST-REx-ID: 8188 | OA
Unsupervised object-centric video generation and decomposition in 3D
P.M. Henderson, C. Lampert, in:, 34th Conference on Neural Information Processing Systems, Curran Associates, 2020, pp. 3106–3117.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2020 | Journal Article | IST-REx-ID: 6952 | OA
Learning single-image 3D reconstruction by generative modelling of shape, pose and shading
P.M. Henderson, V. Ferrari, International Journal of Computer Vision 128 (2020) 835–854.
[Published Version] View | Files available | DOI | WoS | arXiv
 

2020 | Conference Paper | IST-REx-ID: 7936 | OA
Localizing grouped instances for efficient detection in low-resource scenarios
A. Royer, C. Lampert, in:, IEEE Winter Conference on Applications of Computer Vision, IEEE, 2020.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2020 | Conference Paper | IST-REx-ID: 7937 | OA
A flexible selection scheme for minimum-effort transfer learning
A. Royer, C. Lampert, in:, 2020 IEEE Winter Conference on Applications of Computer Vision, IEEE, 2020.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2020 | Book Chapter | IST-REx-ID: 8092 | OA
XGAN: Unsupervised image-to-image translation for many-to-many mappings
A. Royer, K. Bousmalis, S. Gouws, F. Bertsch, I. Mosseri, F. Cole, K. Murphy, in:, R. Singh, M. Vatsa, V.M. Patel, N. Ratha (Eds.), Domain Adaptation for Visual Understanding, Springer Nature, 2020, pp. 33–49.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2020 | Conference Paper | IST-REx-ID: 7481 | OA
Functional vs. parametric equivalence of ReLU networks
M. Phuong, C. Lampert, in:, 8th International Conference on Learning Representations, 2020.
[Published Version] View | Files available
 

2020 | Conference Paper | IST-REx-ID: 8724 | OA
On the sample complexity of adversarial multi-source PAC learning
N.H. Konstantinov, E. Frantar, D.-A. Alistarh, C. Lampert, in:, Proceedings of the 37th International Conference on Machine Learning, ML Research Press, 2020, pp. 5416–5425.
[Published Version] View | Files available | arXiv
 

2020 | Thesis | IST-REx-ID: 8390 | OA
Leveraging structure in Computer Vision tasks for flexible Deep Learning models
A. Royer, Leveraging Structure in Computer Vision Tasks for Flexible Deep Learning Models, Institute of Science and Technology Austria, 2020.
[Published Version] View | Files available | DOI
 

2020 | Conference Paper | IST-REx-ID: 8186 | OA
Leveraging 2D data to learn textured 3D mesh generation
P.M. Henderson, V. Tsiminaki, C. Lampert, in:, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2020, pp. 7498–7507.
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | arXiv
 

2020 | Journal Article | IST-REx-ID: 6944 | OA
KS(conf): A light-weight test if a multiclass classifier operates outside of its specifications
R. Sun, C. Lampert, International Journal of Computer Vision 128 (2020) 970–995.
[Published Version] View | Files available | DOI | WoS
 

2019 | Book (Editor) | IST-REx-ID: 7171
Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt
K. Kersting, C. Lampert, C. Rothkopf, eds., Wie Maschinen Lernen: Künstliche Intelligenz Verständlich Erklärt, 1st ed., Springer Nature, Wiesbaden, 2019.
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2019 | Conference Paper | IST-REx-ID: 6942 | OA
Strategy representation by decision trees with linear classifiers
P. Ashok, T. Brázdil, K. Chatterjee, J. Křetínský, C. Lampert, V. Toman, in:, 16th International Conference on Quantitative Evaluation of Systems, Springer Nature, 2019, pp. 109–128.
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2019 | Journal Article | IST-REx-ID: 6554 | OA
Zero-shot learning - A comprehensive evaluation of the good, the bad and the ugly
Y. Xian, C. Lampert, B. Schiele, Z. Akata, IEEE Transactions on Pattern Analysis and Machine Intelligence 41 (2019) 2251–2265.
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2019 | Conference Paper | IST-REx-ID: 7479 | OA
Distillation-based training for multi-exit architectures
M. Phuong, C. Lampert, in:, IEEE International Conference on Computer Vision, IEEE, 2019, pp. 1355–1364.
[Submitted Version] View | Files available | DOI | WoS
 

2019 | Conference Paper | IST-REx-ID: 7640 | OA
Detecting visual relationships using box attention
A. Kolesnikov, A. Kuznetsova, C. Lampert, V. Ferrari, in:, Proceedings of the 2019 International Conference on Computer Vision Workshop, IEEE, 2019.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Conference Paper | IST-REx-ID: 6569 | OA
Towards understanding knowledge distillation
M. Phuong, C. Lampert, in:, Proceedings of the 36th International Conference on Machine Learning, ML Research Press, 2019, pp. 5142–5151.
[Published Version] View | Files available
 

2019 | Conference Paper | IST-REx-ID: 6590 | OA
Robust learning from untrusted sources
N.H. Konstantinov, C. Lampert, in:, Proceedings of the 36th International Conference on Machine Learning, ML Research Press, 2019, pp. 3488–3498.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2019 | Conference Paper | IST-REx-ID: 6482 | OA
KS(conf): A light-weight test if a ConvNet operates outside of Its specifications
R. Sun, C. Lampert, in:, Springer Nature, 2019, pp. 244–259.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2018 | Thesis | IST-REx-ID: 68 | OA
Learning from dependent data
A. Zimin, Learning from Dependent Data, Institute of Science and Technology Austria, 2018.
[Published Version] View | Files available | DOI
 

2018 | Thesis | IST-REx-ID: 197 | OA
Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images
A. Kolesnikov, Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images, Institute of Science and Technology Austria, 2018.
[Published Version] View | Files available | DOI
 

2018 | Journal Article | IST-REx-ID: 563 | OA
Estimating barriers to gene flow from distorted isolation-by-distance patterns
H. Ringbauer, A. Kolesnikov, D. Field, N.H. Barton, Genetics 208 (2018) 1231–1245.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS
 

2018 | Journal Article | IST-REx-ID: 321 | OA
Guest editors' introduction to the special section on learning with Shared information for computer vision and multimedia analysis
T. Darrell, C. Lampert, N. Sebe, Y. Wu, Y. Yan, IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (2018) 1029–1031.
[Published Version] View | Files available | DOI | WoS
 

2018 | Conference Paper | IST-REx-ID: 10882 | OA
Learning intelligent dialogs for bounding box annotation
J. Uijlings, K. Konyushkova, C. Lampert, V. Ferrari, in:, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018, pp. 9175–9184.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2018 | Conference Paper | IST-REx-ID: 6012 | OA
Learning equations for extrapolation and control
S. Sahoo, C. Lampert, G.S. Martius, in:, Proceedings of the 35th International Conference on Machine Learning, ML Research Press, 2018, pp. 4442–4450.
[Preprint] View | Files available | Download Preprint (ext.) | WoS | arXiv
 

2018 | Conference Paper | IST-REx-ID: 6011 | OA
Data-dependent stability of stochastic gradient descent
I. Kuzborskij, C. Lampert, in:, Proceedings of the 35 Th International Conference on Machine Learning, ML Research Press, 2018, pp. 2815–2824.
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2018 | Conference Paper | IST-REx-ID: 6589 | OA
The convergence of sparsified gradient methods
D.-A. Alistarh, T. Hoefler, M. Johansson, N.H. Konstantinov, S. Khirirat, C. Renggli, in:, Advances in Neural Information Processing Systems 31, Neural Information Processing Systems Foundation, 2018, pp. 5973–5983.
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