Dmitri A. Rachkovskij

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Distributed representations were often criticized as inappropriate for encoding of data with a complex structure. However Plate's Holographic Reduced Representations and Kanerva's Binary Spatter Codes are recent schemes that allow on-the-fly encoding of nested compositional structures by real-valued or dense binary vectors of fixed dimensionality. In this(More)
The purpose of the paper is to design and test neural network structures and mechanisms for making use of the information that is contained in the character strings for more correct recognition of the characters constituting these strings. Two neural networks are considered in the paper; both networks are combined into a joint recognition system. The first(More)
We present an approach to similarity-based retrieval from knowledge bases that takes into account both the structure and semantics of knowledge base fragments. Those fragments, or analogues, are represented as sparse binary vectors that allow a computationally efficient estimation of structural and semantic similarity by the vector dot product. We present(More)
A neural network is described which is intended to extract orientation features that should be used for recognition of hand drawn characters. The network partitions the input hand drawn characters into separate line segments (strokes) according to their orientations. The network consists of several neural layers; each layer serves for extracting strokes of(More)
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