5 citations · 18 across the 16 of their papers we have counts for
19 papers
Drift Localization using Conformal Predictions
Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf +1
Concept drift -- the change of the distribution over time -- poses significant challenges for learning systems and is of central interest for monitoring. Understanding drift is thu…
Large Language Models Do Not Simulate Human Psychology
Sarah Schröder, Thekla Morgenroth, Ulrike Kuhl +2
Large Language Models (LLMs),such as ChatGPT, are increasingly used in research, ranging from simple writing assistance to complex data annotation tasks. Recently, some research ha…
Causal Explanation of Concept Drift -- A Truly Actionable Approach
David Komnick, Kathrin Lammers, Barbara Hammer +2
In a world that constantly changes, it is crucial to understand how those changes impact different systems, such as industrial manufacturing or critical infrastructure. Explaining…
Continuous Fair SMOTE -- Fairness-Aware Stream Learning from Imbalanced Data
Kathrin Lammers, Valerie Vaquet, Barbara Hammer
As machine learning is increasingly applied in an online fashion to deal with evolving data streams, the fairness of these algorithms is a matter of growing ethical and legal conce…
An Algorithm-Centered Approach To Model Streaming Data
Fabian Hinder, Valerie Vaquet, David Komnick +1
Besides the classical offline setup of machine learning, stream learning constitutes a well-established setup where data arrives over time in potentially non-stationary environment…
Adversarial Attacks for Drift Detection
Fabian Hinder, Valerie Vaquet, Barbara Hammer
Concept drift refers to the change of data distributions over time. While drift poses a challenge for learning models, requiring their continual adaption, it is also relevant in sy…