no code implementations • 19 Mar 2024 • Anna Kozak, Dominik Kędzierski, Jakub Piwko, Malwina Wojewoda, Katarzyna Woźnica
In many applications, model ensembling proves to be better than a single predictive model.
1 code implementation • 7 Mar 2024 • Dawid Płudowski, Antoni Zajko, Anna Kozak, Katarzyna Woźnica
In this work, we evaluate Dataset2Vec and liltab on two common meta-tasks - representing entire datasets and hyperparameter optimization warm-start.
1 code implementation • 20 Jun 2023 • Katarzyna Woźnica, Piotr Wilczyński, Przemysław Biecek
In this paper, we present an example of SeFNet prepared for a collection of predictive tasks in healthcare, with the features' relations derived from the SNOMED-CT ontology.
1 code implementation • 27 Jan 2022 • Katarzyna Woźnica, Mateusz Grzyb, Zuzanna Trafas, Przemysław Biecek
For many machine learning models, a choice of hyperparameters is a crucial step towards achieving high performance.
no code implementations • 28 May 2021 • Katarzyna Woźnica, Katarzyna Pękala, Hubert Baniecki, Wojciech Kretowicz, Elżbieta Sienkiewicz, Przemysław Biecek
The increasing number of regulations and expectations of predictive machine learning models, such as so called right to explanation, has led to a large number of methods promising greater interpretability.
BIG-bench Machine Learning Explainable Artificial Intelligence (XAI)
no code implementations • 6 Jul 2020 • Katarzyna Woźnica, Przemysław Biecek
Incomplete data are common in practical applications.
3 code implementations • 2 Jun 2020 • Alicja Gosiewska, Katarzyna Woźnica, Przemysław Biecek
For example, the difference in performance for two models has no probabilistic interpretation, there is no reference point to indicate whether they represent a significant improvement, and it makes no sense to compare such differences between data sets.
no code implementations • 11 Feb 2020 • Katarzyna Woźnica, Przemysław Biecek
are used to predict the expected performance.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +2