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NIPS
2000
13 years 9 months ago
High-temperature Expansions for Learning Models of Nonnegative Data
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
Oliver B. Downs
JMLR
2010
123views more  JMLR 2010»
13 years 3 months ago
Inductive Principles for Restricted Boltzmann Machine Learning
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with in...
Benjamin Marlin, Kevin Swersky, Bo Chen, Nando de ...
JMLR
2010
125views more  JMLR 2010»
13 years 3 months ago
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
Miki Aoyagi
IEAAIE
2001
Springer
14 years 27 days ago
On the Relationship between Learning Capability and the Boltzmann-Formula
In this paper a combined use of reinforcement learning and simulated annealing is treated. Most of the simulated annealing methods suggest using heuristic temperature bounds as the...
Péter Stefán, Laszlo Monostori
VISUALIZATION
2003
IEEE
14 years 1 months ago
Voxels on Fire
We introduce a method for the animation of fire propagation and the burning consumption of objects represented as volumetric data sets. Our method uses a volumetric fire propaga...
Ye Zhao, Xiaoming Wei, Zhe Fan, Arie E. Kaufman, H...