Boltzmann machines

E7922

energy-based model probabilistic graphical model stochastic neural network architecture unsupervised learning model

Boltzmann machines are stochastic recurrent neural networks used for learning complex probability distributions, foundational in unsupervised learning and energy-based models.

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All labels observed (10)

Label	Occurrences
Boltzmann machine	2
Boltzmann machines canonical	2
restricted Boltzmann machines	2
Boltzmann machine learning	1
Deep Boltzmann machines	1
Learning and Relearning in Boltzmann Machines	1
Restricted Boltzmann machines	1
deep Boltzmann machines	1
deep belief networks	1
restricted Boltzmann machine	1

Statements (48)

Predicate	Object
instanceOf	energy-based model ⓘ probabilistic graphical model ⓘ stochastic neural network architecture ⓘ unsupervised learning model ⓘ
approximationMethod	mean-field approximation ⓘ variational inference ⓘ
basedOn	Boltzmann distribution ⓘ statistical mechanics ⓘ
definesProbability	P(s) = exp(-E(s))/Z ⓘ
difficulty	partition function computation is exponential in number of units ⓘ
hasComponent	bias parameters ⓘ hidden units ⓘ visible units ⓘ
hasConnectionType	fully connected between all units in general form ⓘ
hasEnergyFunctionForm	E(v,h) = -∑_i a_i v_i -∑_j b_j h_j -∑_{i,j} v_i w_{ij} h_j -∑_{i<k} v_i u_{ik} v_k -∑_{j<l} h_j v_{jl} h_l ⓘ
hasLearningRule	contrastive divergence approximation ⓘ persistent contrastive divergence ⓘ stochastic gradient descent on log-likelihood ⓘ
hasNetworkType	recurrent neural network ⓘ
hasPartitionFunction	Z = ∑_s exp(-E(s)) ⓘ
hasProperty	Gibbs distribution over states ⓘ Markov random field structure ⓘ asynchronous stochastic updates ⓘ binary-valued units ⓘ converges to thermal equilibrium distribution ⓘ energy function ⓘ intractable exact learning for large networks ⓘ stochastic units ⓘ symmetrical weights ⓘ undirected connections ⓘ
hasSamplingMethod	Gibbs sampling ⓘ Markov chain Monte Carlo ⓘ
inspired	Boltzmann machines self-linksurface differs ⓘ surface form: Deep Boltzmann machines Deep belief networks ⓘ Boltzmann machines self-linksurface differs ⓘ surface form: Restricted Boltzmann machines
introducedBy	Geoffrey Hinton ⓘ Terrence Sejnowski ⓘ
introducedInPublication	Boltzmann machines self-linksurface differs ⓘ surface form: Learning and Relearning in Boltzmann Machines
introducedInYear	1985 ⓘ
relatedTo	Hopfield networks ⓘ Ising models ⓘ
trainingObjective	maximize data log-likelihood ⓘ
usedFor	associative memory ⓘ combinatorial optimization ⓘ density estimation ⓘ modeling complex probability distributions ⓘ representation learning ⓘ unsupervised feature learning ⓘ

Referenced by (13)

Full triples — surface form annotated when it differs from this entity's canonical label.

Geoffrey Hinton → knownFor → Boltzmann machines ⓘ

this entity surface form: restricted Boltzmann machines

Geoffrey Hinton → knownFor → Boltzmann machines ⓘ

this entity surface form: deep belief networks

Boltzmann machines → inspired → Boltzmann machines self-linksurface differs ⓘ

this entity surface form: Restricted Boltzmann machines

Boltzmann machines → inspired → Boltzmann machines self-linksurface differs ⓘ

this entity surface form: Deep Boltzmann machines

Boltzmann machines → introducedInPublication → Boltzmann machines self-linksurface differs ⓘ

this entity surface form: Learning and Relearning in Boltzmann Machines

“A fast learning algorithm for deep belief nets” → usesModel → Boltzmann machines ⓘ

subject surface form: A fast learning algorithm for deep belief nets

this entity surface form: restricted Boltzmann machine

“A fast learning algorithm for deep belief nets” → relatedTo → Boltzmann machines ⓘ

subject surface form: A fast learning algorithm for deep belief nets

Ruslan Salakhutdinov → knownFor → Boltzmann machines ⓘ

this entity surface form: restricted Boltzmann machines

Deep belief networks → relatedTo → Boltzmann machines ⓘ

this entity surface form: deep Boltzmann machines

Terrence Sejnowski → knownFor → Boltzmann machines ⓘ

this entity surface form: Boltzmann machine learning

Hopfield networks → isRelatedTo → Boltzmann machines ⓘ

subject surface form: Hopfield network

this entity surface form: Boltzmann machine

Helmholtz machine → comparedTo → Boltzmann machines ⓘ

this entity surface form: Boltzmann machine