Maryam Amir Haeri

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This paper introduces a new method that improves the generalization ability of genetic programming (GP) for symbolic regression problems, named variance-based layered learning GP. In this approach, several datasets, called primitive training sets, are derived from the original training data. They are generated from less complex to more complex, for a(More)
Nowadays, the emergence of online social networks have empowered people to easily share information and media with friends. Interacting users of social networks with similar users and their friends form community structures of networks. Uncovering communities of the online users in social networks plays an important role in network analysis with many(More)
Mutual Information (MI) is an important dependency measure between random variables, due to its tight connection with information theory. It has numerous applications, both in theory and practice. However, when employed in practice, it is often necessary to estimate the MI from available data. There are several methods to approximate the MI, but arguably(More)
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