← Back to papers
2011 AISTATS AISTATS 2011

Discussion of “Learning Scale Free Networks by Reweighted $\ell_1$ regularization”

Abstract

Discussion of Learning Scale Free Networks by Reweighted $\ell_1$ regularization.

🐝 Cross-Pollinator — Artificial Intelligence, Data Science & Analytics, Healthcare & Medicine, Machine Learning, Mathematics & Optimization

Authors

Deepak Agarwal

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Core Methods > Graphical Models

Keywords

sparse estimation network inference graphical model selection graphical model scale-free network
Download PDF

Related papers

Tighter Relaxations for MAP-MRF Inference: A Local Primal-Dual Gap based Separation Algorithm 2011
Deep Learners Benefit More from Out-of-Distribution Examples 2011
Bagged Structure Learning of Bayesian Network 2011
Convergent Decomposition Solvers for Tree-reweighted Free Energies 2011
Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization 2011