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Soft-Deep Boltzmann Machines
We show that sDBMs can more efficiently exploit the distributed representations in terms of the measure.
Variational Optimization of Annealing Schedules
Annealed importance sampling (AIS) is a common algorithm to estimate partition functions of useful stochastic models.
Approximated Infomax Early Stopping: Revisiting Gaussian RBMs on Natural Images
We pursue an early stopping technique that helps Gaussian Restricted Boltzmann Machines (GRBMs) to gain good natural image representations in terms of overcompleteness and data fitting.
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