Exceptional in so Many Ways—Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios

Autor: Jose Maria Luna, Mykola Pechenizkiy, Wouter Duivesteijn, Sebastian Ventura

Publikováno v: IEEE Access, Vol 8, Pp 200982-200994 (2020)

The current state of the art in supervised descriptive pattern mining is very good in automatically finding subsets of the dataset at hand that are exceptional in some sense. The most common form, subgroup discovery, generally finds subgroups where a

Externí odkaz: https://doaj.org/article/4664961fabd646738195e5089347bb2c

Adversarial balancing-based representation learning for causal effect inference with observational data

Autor: Lei Sun, Alexander G. Nikolaev, Xin Du, Mykola Pechenizkiy, Wouter Duivesteijn

Publikováno v: Pure TUe
arXiv. Cornell University Library
arXiv
Data Mining and Knowledge Discovery, 35(4), 1713-1738. Springer Open
Du, X, Sun, L, Duivesteijn, W, Nikolaev, A & Pechenizkiy, M 2021, ' Adversarial balancing-based representation learning for causal effect inference with observational data ', Data Mining and Knowledge Discovery, vol. 35, no. 4, pp. 1713-1738 . https://doi.org/10.1007/s10618-021-00759-3

Learning causal effects from observational data greatly benefits a variety of domains such as health care, education, and sociology. For instance, one could estimate the impact of a new drug on specific individuals to assist clinical planning and imp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f8e2d709599fc5e513e77d5d7b9942c
https://doi.org/10.1007/s10618-021-00759-3

Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS)

Autor: Rianne Margaretha Schouten, Wouter Duivesteijn, Mykola Pechenizkiy

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c59ee01c873ee298db3bc2309a57bdb2
https://doi.org/10.1137/1.9781611977172.66

Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling

Autor: Xin Du, Yulong Pei, Mykola Pechenizkiy, Wouter Duivesteijn

Publikováno v: Du, X, Pei, Y, Duivesteijn, W & Pechenizkiy, M 2020, ' Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling ', Data Mining and Knowledge Discovery, vol. 34, no. 5, pp. 1267-1290 . https://doi.org/10.1007/s10618-020-00674-z
Data Mining and Knowledge Discovery, 34(5), 1267-1290. Springer Open

Collective social media provides a vast amount of geo-tagged social posts, which contain various records on spatio-temporal behavior. Modeling spatio-temporal behavior on collective social media is an important task for applications like tourism reco

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a9d9543f7f2e835721e8531d0be03db
https://hdl.handle.net/20.500.11820/a0dc04e2-6fa8-4bd4-91f3-38551767eb39

Fairness in network representation by latent structural heterogeneity in observational data

Autor: Wouter Duivesteijn, Mykola Pechenizkiy, Yulong Pei, Xin Du

Publikováno v: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), 3809-3816
STARTPAGE=3809;ENDPAGE=3816;TITLE=Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020)
AAAI

While recent advances in machine learning put many focuses on fairness of algorithmic decision making, topics about fairness of representation, especially fairness of network representation, are still underexplored. Network representation learning le

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ae39e2a1291c91515740bde747b0dd0
https://research.tue.nl/nl/publications/d9a776ec-cf92-4778-b1fa-18c2b706844b