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检索条件"主题词=parameter and structure learning"
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HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems
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NEURAL NETWORKS 1999年 第9期12卷 1301-1319页
作者: Kim, J Kasabov, N Univ Otago Dept Informat Sci Dunedin New Zealand
This paper proposes an adaptive neuro-fuzzy system, HyFIS (Hybrid neural Fuzzy Inference System), for building and optimising fuzzy models. The proposed model introduces the learning power of neural networks to fuzzy ... 详细信息
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learning factor graphs in polynomial time and sample complexity
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JOURNAL OF MACHINE learning RESEARCH 2006年 第8期7卷 1743-1788页
作者: Abbeel, Pieter Koller, Daphne Ng, Andrew Y. Stanford Univ Dept Comp Sci Stanford CA 94305 USA
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree can be learned in polynomial time and... 详细信息
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