Random sum-product forests, ensembles of randomly generated SPNs, beat single random SPNs on binary density-estimation benchmarks, and residual links usually improve the ensemble further.
Markov network structure learning: A randomized feature generation approach
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Random Sum-Product Forests with Residual Links
Random sum-product forests, ensembles of randomly generated SPNs, beat single random SPNs on binary density-estimation benchmarks, and residual links usually improve the ensemble further.