6 citations · 9 across the 8 of their papers we have counts for
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stat.ML2020
Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models
Antoine Dedieu, Miguel Lázaro-Gredilla, Dileep George
We consider the problem of learning the underlying graph of a sparse Ising model with nodes from i.i.d. samples. The most recent and best performing approaches combine an e…
stat.ML2020
Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables
Miguel Lázaro-Gredilla, Wolfgang Lehrach, Nishad Gothoskar +3
Probabilistic graphical models (PGMs) provide a compact representation of knowledge that can be queried in a flexible way: after learning the parameters of a graphical model once,…