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	1. A Fast Greedy Algorithm for Outlier Mining
	zengyou he
	Computer Science and Technology 28 July 2005
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	Abstract:The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. In [38], the problem of outlier detection in categorical data is defined as an optimization problem and a local-search heuristic based algorithm (LSA) is presented. However, as is the case with most iterative type algorithms, the LSA algorithm is still very time-consuming on very large datasets. In this paper, we present a very fast greedy algorithm for mining outliers under the same optimization model. Experimental results on real datasets and large synthetic datasets show that: (1) Our algorithm has comparable performance with respect to those state-of-art outlier detection algorithms on identifying true outliers and (2) Our algorithm can be an order of magnitude faster than LSA algorithm.
	TO cite this article:zengyou he. A Fast Greedy Algorithm for Outlier Mining[OL].[28 July 2005] http://en.paper.edu.cn/en_releasepaper/content/2548


	2. Equivalence of Classification and Regression under Support Vector Machine Theory
	Chunguo Wu,Yanchun Liang
	Computer Science and Technology 17 June 2005
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	Abstract:This paper proposes a novel classification method based on regression. Thereafter, the equivalence of the classification and regression is demonstrated by using numerical experiments. The proposed regression-based classification method can differentiate all samples belonging to different categories concurrently.
	TO cite this article:Chunguo Wu,Yanchun Liang. Equivalence of Classification and Regression under Support Vector Machine Theory[OL].[17 June 2005] http://en.paper.edu.cn/en_releasepaper/content/2223

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	3. A Unified Subspace Outlier Ensemble Framework for Outlier Detection
	zengyou he,Xiaofei Xu
	Computer Science and Technology 25 May 2005
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	Abstract:he task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. Detection of such outliers is important for many applications such as fraud detection and customer migration. Most such applications are high dimensional domains in which the data may contain hundreds of dimensions. However, the outlier detection problem itself is not well defined and none of the existing definitions are widely accepted, especially in high dimensional space. In this paper, our first contribution is to propose a unified framework for outlier detection in high dimensional spaces from an ensemble-learning viewpoint. In our new framework, the outlying-ness of each data object is measured by fusing outlier factors in different subspaces using a combination function. Accordingly, we show that all existing researches on outlier detection can be regarded as special cases in the unified framework with respect to the set of subspaces consider
	TO cite this article:zengyou he,Xiaofei Xu. A Unified Subspace Outlier Ensemble Framework for Outlier Detection[OL].[25 May 2005] http://en.paper.edu.cn/en_releasepaper/content/2107


	4. Evolutionary Algorithm Based on Overlapped Gene Expression
	PENG Jing,TANG Chang-jie,ZHANG Jing,YUAN Chang-an
	Computer Science and Technology 24 May 2005
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	Abstract:. Inspired by the overlap gene expression in biological study, this paper proposes a novel evolutionary algorithm-EAOGE i.e. Evolutionary Algorithm based on Overlapped Gene Expression. Different from existing works, EAOGE suggests a new expression structure of genes with probabilities of overlapped expression for some segments. The main contributions are: (1) Proposing a novel model and an algorithm of gene expression while borrowing some ideas from artificial immunity algorithm; (2) Analyzing the expressing space and encode characteristic of the new model; (3) The extensive experiments in function finding shows that new model is 2.8~9.7 times faster than usual GEP method, and in higher-degree polynomial function finding, the success rate of EAOGE is over 10 times than usual GEP.
	TO cite this article:PENG Jing,TANG Chang-jie,ZHANG Jing, et al. Evolutionary Algorithm Based on Overlapped Gene Expression[OL].[24 May 2005] http://en.paper.edu.cn/en_releasepaper/content/2094


	5. MPRML detection for the readouts of photometric multi-wavelength optical disks
	JIAN Jiqi
	Computer Science and Technology 10 May 2005
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	Abstract:Based on the readout and crosstalk analysis, a kind of multi-channel PRML detection method which is suitable for photometric multi-wavelength optical disks has been brought forward in the paper. The proper PR mode and parameters have been discussed and the optimal solution has been given. Matlab simulation shows that the MPRML method is useful to improve BER performance and the optimal solution is validated. Te experiments on the FPGA-based development board also show that MPRML is applicable for photometric multi-wavelength optical disks.
	TO cite this article:JIAN Jiqi. MPRML detection for the readouts of photometric multi-wavelength optical disks[OL].[10 May 2005] http://en.paper.edu.cn/en_releasepaper/content/2011


	6. An Optimization Model for Outlier Detection in Categorical Data
	Zengyou He
	Computer Science and Technology 31 March 2005
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	Abstract:The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. Detection of such outliers is important for many applications such as fraud detection and customer migration. Most existing methods are designed for numeric data. They will encounter problems with real-life applications that contain categorical data. In this paper, we formally define the problem of outlier detection in categorical data as an optimization problem from a global viewpoint. Moreover, we present a local-search heuristic based algorithm for efficiently finding feasible solutions. Experimental results on real datasets and large synthetic datasets demonstrate the superiority of our model and algorithm.
	TO cite this article:Zengyou He. An Optimization Model for Outlier Detection in Categorical Data[OL].[31 March 2005] http://en.paper.edu.cn/en_releasepaper/content/1768


	7. Mining Top-k Approximate Frequent Patterns
	zengyou he
	Computer Science and Technology 18 March 2005
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	Abstract:requent pattern (itemset) mining in transactional databases is one of the most well-studied problems in data mining. One obstacle that limits the practical usage of frequent pattern mining is the extremely large number of patterns generated. Such a large size of the output collection makes it difficult for users to understand and use in practice. Even restricting the output to the border of the frequent itemset collection does not help much in alleviating the problem. In this paper we address the issue of overwhelmingly large output size by introducing and studying the following problem: mining top-k approximate frequent patterns. The union of the power sets of these k sets should satisfy the following conditions: (1) including itemsets with larger support as many as possible and (2) including itemsets with smaller support as few as possible. An integrated objective function is designed to combine these two objectives. Consequently, we derive the upper bounds on objective function an
	TO cite this article:zengyou he. Mining Top-k Approximate Frequent Patterns[OL].[18 March 2005] http://en.paper.edu.cn/en_releasepaper/content/1725


	8. An-OARSMan: An Obstacle-Avoiding Rectilinear Steiner Tree Algorithm with Good Length Performance
	Yu Hu,Tong Jing,Xianlong Hong,feng zhe,hu xiaodong,yan guiying
	Computer Science and Technology 01 February 2005
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	Abstract:Routing is one of the important steps in VLSI/ULSI physical design. The rectilinear Steiner minimal tree (RSMT) construction is an essential part of routing. Since macro cells, IP blocks, and pre-routed nets are often regarded as obstacles in the routing phase, obstacle-avoiding RSMT (OARSMT) algorithms are useful for practical routing applications. This paper focuses on the OARSMT problem and presents an algorithm, named An-OARSMan, based on ant colony optimization. A greedy obstacle penalty distance (OP-distance) local heuristic is used in the algorithm and performed on the track graph. The algorithm has been implemented and tested on different kinds of obstacles. Experimental results show that An-OARSMan can handle complex obstacle cases including both convex and concave polygon obstacles with good length performance. It can always achieve the optimal solution in the cases with no more than 7 terminals.
	TO cite this article:Yu Hu,Tong Jing,Xianlong Hong, et al. An-OARSMan: An Obstacle-Avoiding Rectilinear Steiner Tree Algorithm with Good Length Performance[OL].[ 1 February 2005] http://en.paper.edu.cn/en_releasepaper/content/1529


	9. FORSTer: An Efficient Heuristic for Obstacle-Avoiding Rectilinear Steiner Tree Construction
	Yu Hu,Zhe Feng,Tong Jing,hong xianlong,yang yang,hu xiaodong,yan guiying
	Computer Science and Technology 01 February 2005
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	Abstract:acro cells, IP blocks, and pre-routed nets are often regarded as obstacles in VLSI routing phase. Obstacle-avoiding rectilinear Steiner minimal tree (OARSMT) algorithms are often used to meet the needs of practical routing applications. However, OARSMT algorithms with multi-terminal nets routing still can not satisfy the requirements of practical applications. This paper presents a 3-step heuristic, named FORSTer, to tackle the OARSMT problem. In Step1, we partition all terminals into some subsets in the presence of obstacles. Then in Step2, we connect terminals in each connected graph with one or more trees, respectively. In Step3, we connect the forest consisting of trees constructed in Step2 into a completed Steiner tree spanning all terminals while avoiding all obstacles. Two algorithms, called ACO-RSMT and GFST-RSMT, are proposed to construct OARSMT in a connected graph in Step2, which are suitable for different situations. This algorithm has been implemented and tested on cases
	TO cite this article:Yu Hu,Zhe Feng,Tong Jing, et al. FORSTer: An Efficient Heuristic for Obstacle-Avoiding Rectilinear Steiner Tree Construction[OL].[ 1 February 2005] http://en.paper.edu.cn/en_releasepaper/content/1528


	10. Multi-layer Mechanism Based Physical Design System Integration
	Yu Hu,Tong Jing,Xianlong Hong
	Computer Science and Technology 31 January 2005
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	Abstract:This paper studies and implements an integrated system for VLSI/ULSI physical design. The multi-layer mechanism is used to get great efficiency and speedup. The physical design system is integrated in three different layers, which are called the data interface layer (DIL), the data management layer (DML) and the data display layer (DDL). A quad-tree data structure is used in DDL to accelerate the graphics showing and the interaction between users and the system.
	TO cite this article:Yu Hu,Tong Jing,Xianlong Hong. Multi-layer Mechanism Based Physical Design System Integration[OL].[31 January 2005] http://en.paper.edu.cn/en_releasepaper/content/1518

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