24 citations · 44 across the 11 of their papers we have counts for
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cs.LG2015
Training a Restricted Boltzmann Machine for Classification by Labeling Model Samples
Malte Probst, Franz Rothlauf
We propose an alternative method for training a classification model. Using the MNIST set of handwritten digits and Restricted Boltzmann Machines, it is possible to reach a classif…
cs.NE2015★ 5 cited
Deep Boltzmann Machines in Estimation of Distribution Algorithms for Combinatorial Optimization
Malte Probst, Franz Rothlauf
Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Deep Boltzmann Machines (DBMs) are generative neural n…