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Abstract—Dimensionality reduction is an important step in knowledge discovery in databases. Intrinsic dimension indicates the number of variables necessary to describe a data set. Two methods, box-counting dimension and correlation dimension, are commonly used for intrinsic dimension estimation. However, the robustness of these two methods has not been rigorously studied. This paper demonstrates that correlation dimension is more robust with respect to data sample size. In addition, instead of using a user selected distance , we propose a n ....etc

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Abstract:
Intel announced a new brand name for its next generation mobile processor technology: Centrino. It was designed to help manufactures to build notebooks that use less power and offer extended battery life along with better wireless networking facilities.


CONTENT
Introduction
Users demand
Notebook PCs: Two Distinct Segments
Configuration
Intel Centrino Mobile Technology
New Centrino technology
Key feature of Intel centrinomobile technology ....etc

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Abstract.
We present a randomized procedure named Hierarchical Sampling from Sketches (HSS) that can be used for estimating a class of functions over the frequency vector f of update streams of the form (S) = Pn i=1 (|fi|).We illustrate this by applying the HSS technique to design nearly space-optimal algorithms for estimating the pth moment of the frequency vector, for real p _ 2 and for estimating the entropy of a data stream. 3
1 Introduction
A variety of applications in diverse areas, such as, networking, database sys ....etc

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IDR-QR: Incremental Dimension Reduction Algorithm via QR Decomposition (Java)
IEEE Transactions on Knowledge and Data Engineering, Vol. 17, No. 9,

Abstract:
Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the literature, a well-known dimension reduction algorithm is Linear Discriminant Analysis (LDA). The common aspect of previously proposed LDA-based algorithms is the use of Singular Value Decomposition ( ....etc

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ppt on data security using neural netwwork and numerical function
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