In the initialization of the traditional semi-supervised k-means, the mean of some labeled data belonging to one same class was regarded as one initial center and the number of the initial centers is equal to the numb...
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High-Ievel programming and programmable data paths are two key capabilities of software-defined networking (SDN). A fundamental problem linking these two capabilities is whether a given high-level SDN program can be r...
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Indentification of informative gene subsets responsible for discerning between available samples of gene expression data is an important task in bioinformatics. Reducts, from rough sets theory, corresponding to a mini...
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This paper proposes a novel adaptive interpolation filter (AIF) to reduce computational complexity and bit-rate of video coding. In the proposed AIF, the filter coefficients of B frames, which are predicted from those...
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Reusing existing class libraries can improve the productivity of software development. API usage patterns are useful resources for programmers in reusing class libraries. Existing approaches often exploit API graphs t...
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A primary challenge for visual-based Reinforcement Learning (RL) is to generalize effectively across unseen environments. Although previous studies have explored different auxiliary tasks to enhance generalization, fe...
Gene selection, a key procedure of the discriminant analysis of microarray data, is to select the most informative genes from the whole gene set. Rough set theory is a mathematical tool for further reducing redundancy...
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This paper is concerned with the problems of H-two filtering for discrete-time Markovian jump linear systems subject to logarithmic quantization. We assume that only the output of the system is available, and therefor...
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This paper is concerned with the problems of H-two filtering for discrete-time Markovian jump linear systems subject to logarithmic quantization. We assume that only the output of the system is available, and therefore the mode information is nonaccessible. In this paper, a mode-independent quantized H-two filter is designed such that filter error system is stochastically stable. To this end, sufficient conditions for the existence of an upper bound of H-two norm are presented in terms of linear matrix inequalities. Considering uncertainty of system matrices, a robust H-two filter is designed. The proposed method is also applicable to cover the case where the transition probability matrix is not exactly known but belongs to a given polytope. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed approach.
service-oriented computing is a new software development paradigm that allows application developers to select available services from the Internet and to form new web services. A main problem is how to efficiently de...
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The task for the data mining contest organized in conjunction with the ICONIP2011 conference was to learn three predictive models (i.e. a classifier) capable of distinguishing between different classes for three separ...
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ISBN:
(纸本)9781849195386
The task for the data mining contest organized in conjunction with the ICONIP2011 conference was to learn three predictive models (i.e. a classifier) capable of distinguishing between different classes for three separate tasks. Different combinations of data preprocess, feature selection and classifier learning methods were tried to obtain the best results.
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