10 citations · 29 across the 20 of their papers we have counts for
13 papers · 1 filter
Convex Mixed-Integer Programming for Causal Additive Models with Optimization and Statistical Guarantees
Xiaozhu Zhang, Nir Keret, Ali Shojaie +1
We study the problem of learning a directed acyclic graph from data generated according to an additive, non-linear structural equation model with Gaussian noise. We express each no…
Consensus Tree Estimation with False Discovery Control via Partially Ordered Sets
Maria Alejandra Valdez Cabrera, Amy D Willis, Armeen Taeb
Trees are data objects that hierarchically organize categories. Collections of trees arise in a diverse variety of fields, including evolutionary biology, machine learning, social…
Quantifying uncertainty and stability among highly correlated predictors: a subspace perspective
Xiaozhu Zhang, Jacob Bien, Armeen Taeb
We study the problem of linear feature selection when features are highly correlated. Such settings pose two fundamental challenges. First, how should model similarity be defined?…
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models
Tong Xu, Armeen Taeb, Simge Küçükyavuz +1
We study the problem of learning directed acyclic graphs from continuous observational data, generated according to a linear Gaussian structural equation model. State-of-the-art st…
Extremal graphical modeling with latent variables via convex optimization
Sebastian Engelke, Armeen Taeb
Extremal graphical models encode the conditional independence structure of multivariate extremes and provide a powerful tool for quantifying the risk of rare events. Prior work on…
Model Selection over Partially Ordered Sets
Armeen Taeb, Peter Bühlmann, Venkat Chandrasekaran
In problems such as variable selection and graph estimation, models are characterized by Boolean logical structure such as presence or absence of a variable or an edge. Consequentl…