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- Tensor_product_network abstract "A tensor product network, in neural networks, is a network that exploits the properties of tensors to model associative concepts such as variable assignment. Orthonormal vectors are chosen to model the ideas (such as variable names and target assignments), and the tensor product of these vectors construct a network whose mathematical properties allow the user to easily extract the association from it.Ranked TensorsA rank 2 tensor can store an arbitrary binary relationTeaching ModeThe network learns which variables have fillers (symbols) when vectors representing a variable and a filler are presented to the two sides of the networkThe teaching is one-shot (vs iterative learning used by backprop & other settling schemes), whereby nothing is annealed or repeatedly adjusted, and no stopping criterion appliesMethodTeaching is accomplished by adjusting the value of the binding unit memory.If the i-th component of the filler vector is fi and the j-th component of the variable vector is vjThen fivj is added to bij (the (i,j)-th binding unit memory) for each i and jSimilarly, regard the binding units as a matrix B, and the filler and variable as column vectors f and v. Then what we are doing is forming the outer product fvT and adding it to BB'=B+fvTRetrieval ModeFor exact retrieval:Vectors used to represent variables & fillers must be orthogonal to each otherRefer to these sets of vectors as an orthonormal setAs such, these vectors are linearly independentIf the matrix/tensor has m rows and n columns, then it can represent at most m fillers and n variablesMethodRetrieval is accomplished by computing dot productsTo retrieve the value/filler for a variable (vj) from a rank 2 tensor with binding unit values bij:compute fi=jbijvj for each i, where the resulting vector fi represents the fillerTo compute whether variable variable (vj) has filler (fi):computer D=ijbijvjfi, where D is a boolean (1 or 0)".
- Tensor_product_network wikiPageID "5099023".
- Tensor_product_network wikiPageRevisionID "532110679".
- Tensor_product_network hasPhotoCollection Tensor_product_network.
- Tensor_product_network subject Category:Neural_networks.
- Tensor_product_network type Abstraction100002137.
- Tensor_product_network type Communication100033020.
- Tensor_product_network type ComputerArchitecture106725249.
- Tensor_product_network type Description106724763.
- Tensor_product_network type Message106598915.
- Tensor_product_network type NeuralNetwork106725467.
- Tensor_product_network type NeuralNetworks.
- Tensor_product_network type Specification106725067.
- Tensor_product_network type Statement106722453.
- Tensor_product_network comment "A tensor product network, in neural networks, is a network that exploits the properties of tensors to model associative concepts such as variable assignment.".
- Tensor_product_network label "Tensor product network".
- Tensor_product_network sameAs m.0d2lnw.
- Tensor_product_network sameAs Q7700712.
- Tensor_product_network sameAs Q7700712.
- Tensor_product_network sameAs Tensor_product_network.
- Tensor_product_network wasDerivedFrom Tensor_product_network?oldid=532110679.
- Tensor_product_network isPrimaryTopicOf Tensor_product_network.