Title :
Holographic reduced representations
Author_Institution :
British Columbia Cancer Res. Centre, Vancouver, BC, Canada
fDate :
5/1/1995 12:00:00 AM
Abstract :
Associative memories are conventionally used to represent data with very simple structure: sets of pairs of vectors. This paper describes a method for representing more complex compositional structure in distributed representations. The method uses circular convolution to associate items, which are represented by vectors. Arbitrary variable bindings, short sequences of various lengths, simple frame-like structures, and reduced representations can be represented in a fixed width vector. These representations are items in their own right and can be used in constructing compositional structures. The noisy reconstructions extracted from convolution memories can be cleaned up by using a separate associative memory that has good reconstructive properties
Keywords :
associative processing; content-addressable storage; convolution; holographic storage; neural nets; associative memory; circular convolution; compositional structures; holographic reduced representations; neural nets; vectors; Artificial intelligence; Associative memory; Cancer; Concrete; Convolution; Councils; Degradation; Holography; Tree data structures;
Journal_Title :
Neural Networks, IEEE Transactions on