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Research map / Graph learning / Graph algorithms and clustering

Structure Learning with Side Information: Sample Complexity

NeurIPS 2019 · Graph learning › Graph algorithms and clustering · approach: Continuous DAG structure learning · 4 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
increase distortion tolerance d in recovered graphML decoder · Simulated Ising graphs, p in [50,500], alpha=20, eta=0.5, n=40probability of errorHelped
increase graph size p with number of edges k fixedML decoder · Simulated Ising graphs, alpha=20, eta=0.5, n=40probability of errorHurt

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