A quantification-based method for the estimation of algorithmic fairness
ql4facct is a software for replicating experiments concerning the evaluation of estimators of classifier "fairness".
Welcome to the AI Assets Catalog! Here you can browse, search and download all the assets currently indexed in the AI-on-Demand platform, including AI libraries, datasets, containers, and more. You are welcome to publish your own AI assets here! To do so, log in in to the platform, go to your dashboard and use the Submit new content button to access the submission forms.
ql4facct is a software for replicating experiments concerning the evaluation of estimators of classifier "fairness".
This data set comprises a labeled training set, validation samples, and testing samples for ordinal quantification. It appears in our research paper "Ordinal Quantification Through Regularization", which we have published at ECML-PKDD 2022.
The aim of the LeQua 2022 dataset is to allow the comparative evaluation of methods for “learning to quantify” in textual datasets, i.e., methods for training predictors of the relative frequencies of the classes of interest in sets of unlabelled textual ...
This record consists of several scripts and files designed to calculate and visualize the efficiency of a burner, as well as predict the burner power using a neural network model. This model consists of a sequential neural network with multiple layers. Bo...
Semantical production description using OWL ontologies as enabler for semantic matchmaking.
Advanced data-driven techniques for better insight into industrial production processes and their optimization
Advanced automated design of simulation models and their use of soft-sensors
A masked contrastive learning framework for learning meaningful fine-grained representations with coarse-labeled dataset.
A self-supervised learning method aiming to alleviate the inherent false-negative problem in contrastive learning framework.
A robust and efficient training framework tackling with dataset with noisy labels.