A new directed tree structure learning framework for zero-inflated compositional nodes uses KL divergence scoring and column-stochastic transition matrices for conditional expectations, with proven consistency and finite-sample guarantees.
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Structure Learning for Directed Trees with Zero-Inflated Compositional Nodes
A new directed tree structure learning framework for zero-inflated compositional nodes uses KL divergence scoring and column-stochastic transition matrices for conditional expectations, with proven consistency and finite-sample guarantees.