activity
20182021
most citedExplaining the Explainer: A First Theoretical Analysis of LIME

51 citations · 52 across the 2 of their papers we have counts for

collaborators

6 papers

stat.CO20211 cited

Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition

Simon Bartels, Wouter Boomsma, Jes Frellsen +1

Algorithms involving Gaussian processes or determinantal point processes typically require computing the determinant of a kernel matrix. Frequently, the latter is computed from the…

cs.LG2021

What does LIME really see in images?

Damien Garreau, Dina Mardaoui

The performance of modern algorithms on certain computer vision tasks such as object recognition is now close to that of humans. This success was achieved at the price of complicat…

stat.ML2020

An Analysis of LIME for Text Data

Dina Mardaoui, Damien Garreau

Text data are increasingly handled in an automated fashion by machine learning algorithms. But the models handling these data are not always well-understood due to their complexity…

cs.LG202051 cited

Explaining the Explainer: A First Theoretical Analysis of LIME

Damien Garreau, Ulrike von Luxburg

Machine learning is used more and more often for sensitive applications, sometimes replacing humans in critical decision-making processes. As such, interpretability of these algori…

stat.ML2018

Comparison-Based Random Forests

Siavash Haghiri, Damien Garreau, Ulrike von Luxburg

Assume we are given a set of items from a general metric space, but we neither have access to the representation of the data nor to the distances between data points. Instead, supp…

cs.LG2018

NEWMA: a new method for scalable model-free online change-point detection

Nicolas Keriven, Damien Garreau, Iacopo Poli

We consider the problem of detecting abrupt changes in the distribution of a multi-dimensional time series, with limited computing power and memory. In this paper, we propose a new…