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Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
In 2010, Tomáš Mikolov (then at Brno University of Technology) with co-authors applied a simple recurrent neural network with a single hidden layer to language modelling. [ 6 ] Word2vec was created, patented, [ 7 ] and published in 2013 by a team of researchers led by Mikolov at Google over two papers.
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or mathematical models . While individual neurons are simple, many of them together in a network can perform complex tasks.
Capsule neural network; Catastrophic interference; Cellular neural network; Cerebellar model articulation controller; CoDi; Committee machine; Competitive learning; Compositional pattern-producing network; Computational cybernetics; Computational neurogenetic modeling; Confabulation (neural networks) Connectionist temporal classification ...
Microsoft Cognitive Toolkit (previously known as CNTK), an open source toolkit for building artificial neural networks. [82] OpenNN, a comprehensive C++ library implementing neural networks. [83] PyTorch, an open-source Tensor and Dynamic neural network in Python. [84] TensorFlow, an open-source software library for machine learning. [85]
Below is a list of notable companies that primarily focuses on artificial intelligence (AI). Companies that simply makes use of AI but have a different primary focus are not included. Companies that simply makes use of AI but have a different primary focus are not included.
An associative neural network has a memory that can coincide with the training set. If new data become available, the network instantly improves its predictive ability and provides data approximation (self-learns) without retraining. Another important feature of ASNN is the possibility to interpret neural network results by analysis of ...
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