data_mining:neural_network:hopfield

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data_mining:neural_network:hopfield [2017/04/09 11:03] – [Improve search with stochastic units] phreazerdata_mining:neural_network:hopfield [2017/04/09 11:10] (current) – [Boltzman machine] phreazer
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 $p(s_i=1) = \frac{1}{1+e^{-\Delta E_i/T}}$ $p(s_i=1) = \frac{1}{1+e^{-\Delta E_i/T}}$
 +
 +===== Thermal equilibrium =====
 +Thermal equi. at temperature of 1
 +
 +Reaching thermal equilibrium is difficult concept. Probability distribution over configurations settles down to statonary distribution.
 +
 +Intuitively: Huge ensemble of systems that have same energy function. Probabiltiy of configuration is just fraction of the systems that have configuration.
 +
 +Approaching equilibrium:
 +
 +* Start with any distribution over all identical systems
 +* Apply stochastic update rule, to pick next configuration for each individual system
 +* May reach situation where fraction of systems in each configuration remains constant.
 +  * This stationary distribution is called thermal equilibrium.
 +  * Any given system keeps changing its configuration, but the fraction of systems in each configuration does not change.
 +
 +===== Boltzman machine =====
 +
 +Given: Training set of binary vectors. Fit model that will assign a probability to every possible binary vector.
 +
 +
 +Useful for deciding if other binary vectors come from some distribution (e.g. to detect unusual behavious).
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  • Last modified: 2017/04/09 11:03
  • by phreazer