6 citations · 7 across the 3 of their papers we have counts for
3 papers
Weighted Contrastive Divergence
Enrique Romero Merino, Ferran Mazzanti Castrillejo, Jordi Delgado Pin +1
Learning algorithms for energy based Boltzmann architectures that rely on gradient descent are in general computationally prohibitive, typically due to the exponential number of te…
A Neighbourhood-Based Stopping Criterion for Contrastive Divergence Learning
E. Romero, F. Mazzanti, J. Delgado
Restricted Boltzmann Machines (RBMs) are general unsupervised learning devices to ascertain generative models of data distributions. RBMs are often trained using the Contrastive Di…
Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error
David Buchaca, Enrique Romero, Ferran Mazzanti +1
Restricted Boltzmann Machines (RBMs) are general unsupervised learning devices to ascertain generative models of data distributions. RBMs are often trained using the Contrastive Di…