Adnan Darwiche

Tractable learning for complex probability queries

2015 · Lirias

Tractable learning aims to learn probabilistic models where inference is guaran-teed to be efficient. However, the particular class of queries that is tractable de-pends on the model and underlying representation. Usually this class is MPE …

Data compression for learning MRF parameters

2015

We propose a technique for decomposing and compressing the dataset in the parameter learning problem in Markov random fields. Our technique applies to incomplete datasets and exploits variables that are always observed in the given …

On the Complexity of Counterfactual Reasoning

2022 · arXiv (Cornell University)

We study the computational complexity of counterfactual reasoning in relation to the complexity of associational and interventional reasoning on structural causal models (SCMs). We show that counterfactual reasoning is no harder than associational or interventional …