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20192022
most citedCounterfactual Explanations of Concept Drift

4 citations · 9 across the 6 of their papers we have counts for

collaborators

10 papers

cs.LG20221 cited

On the Change of Decision Boundaries and Loss in Learning with Concept Drift

Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf +1

The notion of concept drift refers to the phenomenon that the distribution generating the observed data changes over time. If drift is present, machine learning models may become i…

cs.LG2022

Precise Change Point Detection using Spectral Drift Detection

Fabian Hinder, André Artelt, Valerie Vaquet +1

The notion of concept drift refers to the phenomenon that the data generating distribution changes over time; as a consequence machine learning models may become inaccurate and nee…

cs.LG20221 cited

Suitability of Different Metric Choices for Concept Drift Detection

Fabian Hinder, Valerie Vaquet, Barbara Hammer

The notion of concept drift refers to the phenomenon that the distribution, which is underlying the observed data, changes over time; as a consequence machine learning models may b…

cs.LG2021

Contrastive Explanations for Explaining Model Adaptations

André Artelt, Fabian Hinder, Valerie Vaquet +2

Many decision making systems deployed in the real world are not static - a phenomenon known as model adaptation takes place over time. The need for transparency and interpretabilit…

cs.LG2021

Evaluating Robustness of Counterfactual Explanations

André Artelt, Valerie Vaquet, Riza Velioglu +4

Transparency is a fundamental requirement for decision making systems when these should be deployed in the real world. It is usually achieved by providing explanations of the syste…

cs.LG20202 cited

Analysis of Drifting Features

Fabian Hinder, Jonathan Jakob, Barbara Hammer

The notion of concept drift refers to the phenomenon that the distribution, which is underlying the observed data, changes over time. We are interested in an identification of thos…