8 citations · 10 across the 7 of their papers we have counts for
3 papers · 1 filter
Explaining Concept Drift through the Evolution of Group Counterfactuals
Ignacy Stępka, Jerzy Stefanowski
Machine learning models in dynamic environments often suffer from concept drift, where changes in the data distribution degrade performance. While detecting this drift is a well-st…
Mitigating Persistent Client Dropout in Asynchronous Decentralized Federated Learning
Ignacy Stępka, Nicholas Gisolfi, Kacper Trębacz +1
We consider the problem of persistent client dropout in asynchronous Decentralized Federated Learning (DFL). Asynchronicity and decentralization obfuscate information about model u…
DetoxAI: a Python Toolkit for Debiasing Deep Learning Models in Computer Vision
Ignacy Stępka, Lukasz Sztukiewicz, Michał Wiliński +1
While machine learning fairness has made significant progress in recent years, most existing solutions focus on tabular data and are poorly suited for vision-based classification t…