DAG sets threshold

DAG program: identifying minimal sufficient adjustment sets.

A n important source of bias in observational studies is confounding. According to the classic definition of confounding , a factor is a confounder if it is a risk factor for the disease and influences the occurrence of exposure. In addition, the factor must not be affected by the exposure of interest (no intermediate variable). 1,2 The introduction of causal diagrams (directed acyclic graphs, ...

On maximum spanning DAG algorithms for semantic DAG parsing

Consideration of the decoding problem in semantic parsing as finding a maximum spanning DAG of a weighted directed graph carries many complexities that haven’t been fully addressed in the literature to date, among which are its actual appropriateness for the decoding task in semantic parsing, not to mention an explicit proof of its complexity (and its approximability). In this paper, we conside...

Beware of the DAG!

Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a means of extracting causal conclusions from probabilistic conditional independence properties inferred from purely observational data. I take a critical look at this enterprise, and suggest that it is in need of more, ...

Scheduling DAG Structured Computations

On Optimal DAG Reversal

Runs of numerical computer programs can be visualized as directed acyclic graphs (DAGs). We consider the problem of restoring the intermediate values computed by such a program (the vertices in the DAG) in reverse order for a given upper bound on the available memory. The minimization of the associated computational cost in terms of the number of performed arithmetic operations is shown to be N...