Restricted Boltzmann Machines

URI: https://gptkb.org/entity/Restricted_Boltzmann_Machines

GPTKB entity

Statements (50)

Predicate	Object
gptkbp:instanceOf	gptkb:convolutional_neural_network gptkb:Probabilistic_Graphical_Model
gptkbp:activatedBy	gptkb:Sigmoid
gptkbp:canBe	gptkb:Speech_Recognition gptkb:Collaborative_Filtering Image Recognition Topic Modeling Anomaly Detection Data Generation Data Reconstruction Pretraining Neural Networks
gptkbp:canBeTrainedBy	gptkb:Persistent_Contrastive_Divergence Stochastic Gradient Descent
gptkbp:developedBy	gptkb:Geoffrey_Hinton
gptkbp:energyFunction	Yes
gptkbp:extendsTo	gptkb:Gaussian-Bernoulli_RBM gptkb:Replicated_Softmax_RBM
gptkbp:field	gptkb:Machine_Learning gptkb:artificial_intelligence Deep Learning
gptkbp:hasConnectionsBetween	Visible and Hidden Layers
gptkbp:hasHiddenLayer	Yes
gptkbp:hasNoConnectionsBetween	Units in Same Layer
gptkbp:hasVisibleLayer	Yes
https://www.w3.org/2000/01/rdf-schema#label	Restricted Boltzmann Machines
gptkbp:input	Binary
gptkbp:introducedIn	1986
gptkbp:limitation	Approximate Inference Required Difficult to Train for Large Datasets Limited Scalability Sensitive to Hyperparameters
gptkbp:output	Binary
gptkbp:parameter	Weights Biases
gptkbp:popularizedBy	2006
gptkbp:relatedTo	gptkb:Hopfield_Network gptkb:Boltzmann_Machine gptkb:Markov_Random_Field gptkb:Deep_Neural_Network Boltzmann machine
gptkbp:stackable	Yes
gptkbp:trainingAlgorithm	gptkb:Contrastive_Divergence
gptkbp:usedFor	gptkb:Collaborative_Filtering Classification Dimensionality Reduction Feature Learning Pretraining Deep Networks
gptkbp:usedIn	gptkb:Deep_Belief_Networks
gptkbp:bfsParent	gptkb:A_Fast_Learning_Algorithm_for_Deep_Belief_Nets_(Hinton_et_al.,_2006)
gptkbp:bfsLayer	7