23 citations · 48 across the 26 of their papers we have counts for
4 papers · 1 filter
Nonnegative DAG Learning via Concomitant Estimation
Madeline Navarro, Gonzalo Mateos, Samuel Rey
We study the problem of learning directed acyclic graphs (DAGs) with nonnegative edge weights from observational data. We propose the Nonnegative and Concomitant (NoCo) DAG estimat…
Exploiting Non-Negativity in DAG Structure Learning
Samuel Rey, Madeline navarro, Gonzalo Mateos +1
This work addresses the problem of learning directed acyclic graphs (DAGs) from nodal observations adhering to a linear structural equation model. DAG structure learning is a centr…
Fair Feature Importance Scores via Feature Occlusion and Permutation
Camille Little, Madeline Navarro, Santiago Segarra +1
As machine learning models increasingly impact society, their opaque nature poses challenges to trust and accountability, particularly in fairness contexts. Understanding how indiv…
Stationarity and Spectral Characterization of Random Signals on Simplicial Complexes
Madeline Navarro, Andrei Buciulea, Santiago Segarra +1
It is increasingly common for data to possess intricate structure, necessitating new models and analytical tools. Graphs, a prominent type of structure, can encode the relationship…