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State automata extraction from recurrent neural nets using ...
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由 AL Cechin 著作2003被引用 29 次 — Two clustering methods are compared for the automata extraction: the K-means method, and the construction of fuzzy membership functions. It is shown that the ...
State automata extraction from recurrent neural nets using ...
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由 AL Cechin 著作2003被引用 29 次 — In this work, two methods are investigated: one using the K-means clustering method and the other using a fuzzy clustering based on linear relations [5]. From ...
State automata extraction from recurrent neural nets using ...
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A recurrent neural network is used to learn the dynamical behavior of the inverted pendulum and from this network to extract a finite state automata, ...
State automata extraction from recurrent neural nets using k- ...
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Two clustering methods are compared for the automata extraction: the K-means method, and the construction of fuzzy membership functions. It is shown that the ...
State Automata Extraction from Recurrent Neural Nets using k ...
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由 AL Cechin 著作2003被引用 29 次 — This paper presents the use of a recurrent neuralnetwork to learn the dynamical behavior of the invertedpendulum and from this network to extract a finite ...
State Automata Extraction from Recurrent Neural Nets using k- ...
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Bibliographic details on State Automata Extraction from Recurrent Neural Nets using k-Means and Fuzzy Clustering.
Extracting Automata from Neural Networks Using Active ...
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由 Z Xu 著作被引用 6 次 — In this paper, we present an active learning framework to extract automata from neural network classifiers, which can help users to understand the concepts ...
8 頁
[PDF] Extracting Automata from Recurrent Neural Networks ...
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We present a novel algorithm that uses exact learning and abstraction to extract a deterministic finite automaton describing the state dynamics of a given ...
Extracting Automata from Recurrent Neural Networks Using ...
Proceedings of Machine Learning Research
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Proceedings of Machine Learning Research
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由 G Weiss 著作被引用 244 次 — Another approach is to fit an unsupervised classifier such as k-means to a large sample set of reachable network states. (Cechin et al., 2003; Zeng et al., 1993) ...
10 頁
Rule Extraction from Recurrent Neural Networks
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Abstract. Rule extraction (RE) from recurrent neural networks (RNNs) refers to finding models of the underlying RNN, typically in the form of finite state ...