Follow
Damien Garreau
Damien Garreau
Professor for the Theory of Machine Learning, Julius-Maximilians-Universität Würzburg
Verified email at uni-wuerzburg.de - Homepage
Title
Cited by
Cited by
Year
Explaining the Explainer: A First Theoretical Analysis of LIME
D Garreau, U von Luxburg
23rd International Conference on Artificial Intelligence and Statistics 108 …, 2020
2672020
Large sample analysis of the median heuristic
D Garreau, W Jitkrittum, M Kanagawa
arXiv preprint arXiv:1707.07269, 2017
1572017
When do random forests fail?
C Tang, D Garreau, U von Luxburg
Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 2018
1202018
Consistent change-point detection with kernels
D Garreau, S Arlot
Electronic Journal of Statistics 12 (2), 4440-4486, 2018
1052018
Metric learning for temporal sequence alignment
D Garreau, R Lajugie, S Arlot, F Bach
Advances in Neural Information Processing Systems 27 (NeurIPS 2014), 1817-1825, 2014
712014
An analysis of LIME for text data
D Mardaoui, D Garreau
24th International Conference on Artificial Intelligence and Statistics 130 …, 2021
612021
What does LIME really see in images?
D Garreau, D Mardaoui
38th International Conference on Machine Learning 139, 3620-3629, 2021
552021
NEWMA: a new method for scalable model-free online change-point detection
N Keriven, D Garreau, I Poli
IEEE Transactions on Signal Processing 68, 3515-3528, 2020
552020
Looking deeper into tabular LIME
D Garreau, U von Luxburg
arXiv preprint arXiv:2008.11092, 2020
472020
Comparison-Based Random Forests
S Haghiri, D Garreau, U von Luxburg
35th International Conference on Machine Learning 80, 1871-1880, 2018
382018
Dynamics of the knowledge instinct: Effects of incoherence on the cognitive system
F Schoeller, M Eskinazi, D Garreau
Cognitive Systems Research 47, 85-91, 2018
212018
A Sea of Words: An In-Depth Analysis of Anchors for Text Data
G Lopardo, F Precioso, D Garreau
26th International Conference on Artificial Intelligence and Statistics 206 …, 2023
62023
Change-point Detection and Kernel Methods
D Garreau
PSL Research University; ENS Paris-Ecole Normale Supérieure de Paris, 2017
62017
Explainability as statistical inference
HHJ Senetaire, D Garreau, J Frellsen, PA Mattei
40th International Conference on Machine Learning 202, 30584-30612, 2023
42023
Understanding Post-hoc Explainers: The Case of Anchors
G Lopardo, F Precioso, D Garreau
arXiv preprint arXiv:2303.08806, 2023
32023
Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition
S Bartels, W Boomsma, J Frellsen, D Garreau
Journal of Machine Learning Research 24 (71), 1-57, 2023
32023
Interpretable Prediction of Post-Infarct Ventricular Arrhythmia using Graph Convolutional Network
B Ly, S Finsterbach, M Nuñez-Garcia, P Jaïs, D Garreau, H Cochet, ...
STACOM 2022-13th Workshop on Statistical Atlases and Computational Modelling …, 2022
32022
Faithful and Robust Local Interpretability for Textual Predictions
G Lopardo, F Precioso, D Garreau
arXiv preprint arXiv:2311.01605, 2023
22023
On the Robustness of Text Vectorizers
R Catellier, S Vaiter, D Garreau
40th International Conference on Machine Learning 202, 3782-3814, 2023
22023
SMACE: A New Method for the Interpretability of Composite Decision Systems
G Lopardo, D Garreau, F Precioso, G Ottosson
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2022
22022
The system can't perform the operation now. Try again later.
Articles 1–20