4 citations · 10 across the 19 of their papers we have counts for
5 papers · 1 filter
ExMAG: Learning of Maximally Ancestral Graphs
Petr Ryšavý, Pavel Rytíř, Xiaoyu He +2
In mixed graphs, there are both directed and bidirected edges. An extension of acyclicity to this mixed-graph setting is known as maximally ancestral graphs. This extension is of c…
Sample Complexity of Bias Detection with Subsampled Point-to-Subspace Distances
German Martinez Matilla, Jakub Marecek
Sample complexity of bias estimation is a lower bound on the runtime of any bias detection method. Many regulatory frameworks require the bias to be tested for all subgroups, whose…
ExDBN: Learning Dynamic Bayesian Networks using Extended Mixed-Integer Programming Formulations
Pavel Rytir, Ales Wodecki, Georgios Korpas +1
Causal learning from data has received much attention recently. Bayesian networks can be used to capture causal relationships. There, one recovers a weighted directed acyclic graph…
Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference
Vyacheslav Kungurtsev, Apaar, Aarya Khandelwal +3
In this work, we demonstrate the Empirical Bayes approach to learning a Dynamic Bayesian Network. By starting with several point estimates of structure and weights, we can use a da…
ExDAG: an MIQP Algorithm for Learning DAGs
Pavel Rytir, Ales Wodecki, Jakub Marecek
There has been a growing interest in causal learning in recent years. Commonly used representations of causal structures, including Bayesian networks and structural equation models…