21 citations · 58 across the 13 of their papers we have counts for
4 papers · 1 filter
Learning linear structural equation models in polynomial time and sample complexity
Asish Ghoshal, Jean Honorio
The problem of learning structural equation models (SEMs) from data is a fundamental problem in causal inference. We develop a new algorithm --- which is computationally and statis…
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity
Asish Ghoshal, Jean Honorio
We consider the problem of learning sparse polymatrix games from observations of strategic interactions. We show that a polynomial time method based on -group regulariz…
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions
Asish Ghoshal, Jean Honorio
In this paper we obtain sufficient and necessary conditions on the number of samples required for exact recovery of the pure-strategy Nash equilibria (PSNE) set of a graphical game…
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity
Asish Ghoshal, Jean Honorio
Learning the directed acyclic graph (DAG) structure of a Bayesian network from observational data is a notoriously difficult problem for which many hardness results are known. In t…