User: Guest  Login
Less Searchfields
Simple search
Title:

causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery

Document type:
Konferenzbeitrag
Contribution type:
Vortrag / Präsentation
Author(s):
Göbler, Konstantin; Windisch, Tobias; Drton, Mathias; Pychynski, Tim; Roth, Martin; Sonntag, Steffen
Pages contribution:
609--642
Abstract:
Algorithms for causal discovery have recently undergone rapid advances and increasingly draw on flexible nonparametric methods to process complex data. With these advances comes a need for adequate empirical validation of the causal relationships learned by different algorithms. However, for most real and complex data sources true causal relations remain unknown. This issue is further compounded by privacy concerns surrounding the release of suitable high-quality data. To tackle these challenges...     »
Keywords:
Causal discovery, benchmarking, production data, distributional random forest
Dewey Decimal Classification:
510 Mathematik
Editor:
MLResearchPress
Book / Congress title:
Proceedings of Machine Learning Research
Congress (additional information):
Third Conference on Causal Learning and Reasoning
Volume:
236
Date of congress:
April 1-3, 2024
Date of publication:
19.03.2024
Year:
2024
Quarter:
1. Quartal
Year / month:
2024-03
Month:
Mar
E-ISBN:
2640-3498
Language:
en
Publication format:
WWW
WWW:
Proceedings of Machine Learning Research
Semester:
WS 23-24
TUM Institution:
Lehrstuhl für Mathematische Statistik
Format:
Text
 BibTeX