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A fast kernel dimension reduction algorithm with applications to face recognition

A fast kernel dimension reduction algorithm with application...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： An Liu Svetha Venkatesh Tjahyadi Department of Computing Curtin University of Technology Perth WA Australia

This paper presents a novel dimensionality reduction algorithm for kernel based classification. In the feature space, the proposed algorithm maximizes the ratio of the squared between-class distance and the sum of the within-class variances of the training samples for a given reduced dimension. This algorithm has lower complexity than the recently reported kernel dimension reduction (KDR) for supervised learning. We conducted several simulations with large training datasets, which demonstrate that the proposed algorithm has similar performance or is marginally better compared with KDR whilst having the advantage of computational efficiency. Further, we applied the proposed dimension reduction algorithm to face recognition in which the number of training samples is very small. This proposed face recognition approach based on the new algorithm outperforms the eigenface approach based on the principle component analysis (PCA), when the training data is complete, that is, representative of the whole dataset.

关键词： Kernel Face recognition Support vector machines Support vector machine classification Noise reduction Space technology Supervised learning Computational modeling Computational efficiency Algorithm design and analysis

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Localized generalization error and its application to RBFNN training

Localized generalization error and its application to RBFNN ...

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international conference on machine learning and Cybernetics (icmlc)

作者： Ng Yeung De-Feng Wang Tsang Xi-Zhao Wang Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong China Machine Learning Center Faculty of Mathematics and Computer Science Hebei University Baoding China

The generalization error bounds for the entire input space found by current error models using the number of effective parameters of a classifier and the number of training samples are usually very loose. But classifiers such as SVM, RBFNN and MLPNN, are really local learning machines used for many application problems, which consider unseen samples close to the training samples more important. In this paper, we propose a localized generalization error model which bounds above the generalization error within a neighborhood of the training samples using stochastic sensitivity measure (expectation of the squared output perturbations). It is then used to develop a model selection technique for a classifier with maximal coverage of unseen samples by specifying a generalization error threshold. Experiments by using eight real world datasets show that, in comparison with cross-validation, sequential learning, and two other ad-hoc methods, our technique consistently yields the best testing classification accuracy with fewer hidden neurons and less training time.

关键词： Analytical models machine learning Support vector machines Support vector machine classification Neural networks Computer errors Pattern classification EMP radiation effects Mathematics Computer science

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A study on parallel semantics of constraint logic programs

A study on parallel semantics of constraint logic programs

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Ji-Gui Sun Yong-Gang Zhang College of Computer Science and Technology Jilin University Changchun China Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China

This paper presents two parallel semantics of constraint logic programs: multiset answer constraint semantics and game semantics, which differ entirely from the traditional semantics. When giving the first semantics, it adopts the s-semantics approach, whose aim is to find notions of models which really capture the operational semantics. And it defines the program equivalence based on multiset answer constraint. Then it investigates the game semantics and proves that it is consistent with traditional operational semantics. On the basis of these two semantics, programmers can comprehend the programs deeply and develop more sound parallel constraint logic programming systems. Finally, it gives the conclusions and future work.

关键词： Logic programming Sun Educational institutions Computer science Educational technology Laboratories Concurrent computing Knowledge engineering Computer science education Educational programs

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Cluster validity for DNA microarray data using a geometrical index

Cluster validity for DNA microarray data using a geometrical...

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international conference on machine learning and Cybernetics (icmlc)

作者： Lam Hong Yan Department of Electronic Engineering City University of Hong Kong Kowloon Hong Kong China School of Electrical and Information Engineering University of Sydney NSW Australia

A number of clustering methods have been used for DNA microarray data analysis. It is an important problem how to evaluate the results of these algorithms. In this paper, we introduce a new cluster validity index, which measures the geometrical feature of the data. The essential concept of this index is to measure the squared total length of the data eigen-axes with respect to the between-cluster separation. We show that this cluster validity index works well for data, which are close together or have different sizes. In our experiments, the proposed index is compared to five other validity indices and experiment results show that the proposed index gives more accurate results.

关键词： DNA Clustering algorithms Data analysis Data engineering Length measurement Clustering methods Pattern classification Biology computing Data mining Cost function

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The Research and Implematation of Services Discovery Agent in Web Services Composition Framework

The Research and Implematation of Services Discovery Agent i...

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international conference on machine learning and Cybernetics (icmlc)

作者： Bin Li Xiao-Yan Tang Jian Lv State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science and Engineering Yangzhou University Yangzhou China

Web services are emerging as a dominant paradigm for constructing and composing distributed business applications and enabling enterprise-wide interoperability. A critical factor to the overall utility of web services composition is a flexible services discovery mechanism. The goal of this paper is to propose an agent-based approach to web services discovery. Firstly, an agent-based framework for web services composition is presented. Next, web services QoS model and description are introduced and an algorithm of selecting services from the perspective of composition is given. Finally, web services discovery agent is designed and its implementation based on JADE platform is presented in detail.

关键词： Web services Quality of service Software agents Application software Middleware Computer science Laboratories Distributed computing Intelligent agent Monitoring

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Mobile decision support in server and mobile terminals

Mobile decision support in server and mobile terminals

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international conference on machine learning and Cybernetics (icmlc)

作者： De-min Li Jie Zhou College of Information Science and Technology Donghua Uinversity Shanghai China School of Sciences Donghua Uinversity Shanghai China

In this paper we consider the mobile decision supports both in server and in mobile terminal. Mobility traces record actual movement behavior of mobile users. We investigate data mining methods to discovery the mobile patterns, and utilize the moving patterns to provide decision schemes of home base station selection, location area selection, the HLR and VLR balance in server. Consider traffic and tele-traffic constrains in mobile environment, we model the mobile decision process for a trip by Markov decision process in mobile terminals. This model is used to optimize the mobile process and provide a mobile decision support for a trip. Some simulations are discussed in the end.

关键词： Decision support systems Mobile computing Mobile communication Network servers Interference constraints Mobile radio mobility management Data mining Traffic control Databases Personal digital assistants

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INC: a new philosophy of CNC

INC: a new philosophy of CNC

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international conference on machine learning and Cybernetics (icmlc)

作者： Tan Liu Tao Yu Shu-Zhen Yang Wen-Bin Wang CIMS & Robot Center Shanghai University Shanghai China Electromechanical Engineering Institute Shanghai Second Polytechnic University Shanghai China

This paper proposes a new philosophy of CNC (computer numerical control), which is named as INC (integrated numerical control or intelligent numerical control). First it has a brief introduction of INC and makes a comparison and analysis about INC, ONC and DNC. Further it describes the important characteristics of INC and introduces the key technologies of INC. And then it emphasizes on discussing some intelligent characteristics of INC, which includes image recognition and vector quantization (VQ), intelligent process planning, simulation, etc. It discusses the principle and application of them in details. Finally, a case is given to illustrate how to realize INC in the engineering area.

关键词： Computer numerical control Computer integrated manufacturing Computer aided manufacturing Materials requirements planning Process planning CADCAM Intelligent robots Telecommunication computing Robot kinematics Technology management

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A heuristic for total flowtime minimization in flow shop scheduling

A heuristic for total flowtime minimization in flow shop sch...

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international conference on machine learning and Cybernetics (icmlc)

作者： Xiang Gao Xiao-Ping Li Hong-Fang Zhang Department of Computer Science & Technology Harbin University of Science and Technology Harbin China Department of Computer Science and Engineering South-East University Nanjing China Department of Information Science Harbin Normal University Harbin China

In this paper, DIH (double inserting heuristic) is proposed for flow shops with total flowtime minimization, in which the initial solution is improved by combing local-insertion with global-insertion. As well, partial inserting selection is introduced to reduce the computation time. DIH is compared with three best existing heuristics, RZ, WY and FL, on 6000 randomly generated instances in both effectiveness and efficiency. Computational results show that DIH is the best in effectiveness and the CPU time of DIH is more than that of WY or RZ but less than that of FL.

关键词： Job shop scheduling Optimal scheduling Processor scheduling Computer science Manufacturing systems Information science Manufacturing industries Polynomials Computer aided manufacturing High performance computing

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Classification of power quality disturbances using wavelet and fuzzy support vector machines

Classification of power quality disturbances using wavelet a...

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international conference on machine learning and Cybernetics (icmlc)

作者： Guo-Sheng Hu Jing Xie Feng-Feng Zhu Electric Power School South China University of Technology Guangzhou China

In this paper, wavelets and fuzzy support vector machines are used to automated detect and classify power quality (PQ) disturbances. Electric power quality is an aspect of power engineering that has been with us since the inception of power systems. The types of concerned disturbances include voltage sags, swells, interruptions, switching transients, impulses, flickers, harmonics, and notches. Fourier transform and wavelet analysis are utilized to denoise the digital signals, to decompose the signals and then to obtain eight common features for the sampling PQ disturbance signals. A fuzzy support vector machines is designed and trained by 8-dimension feature space points for making a decision regarding the type of the disturbance. Simulation cases illustrate the effectiveness.

关键词： Power quality Support vector machines Support vector machine classification Power system harmonics Power system transients Power engineering Power system analysis computing Voltage fluctuations Fourier transforms Wavelet analysis

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Video abrupt shot change detection based on relation of the partial interframe differences

Video abrupt shot change detection based on relation of the ...

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international conference on machine learning and Cybernetics (icmlc)

作者： Sheng-Rong Gong Yi-Jin Fan School of Computer Science and Technology Soochow University Suzhou China

The abrupt shot change detection is a basic and important technology in content-based video retrieval. Some basic algorithms, such as the pixel-matching algorithm, the histogram algorithm, used to detect abrupt shot change in digital video have existed. But the existing algorithms can not eliminate the influence of the video movement. When much video movement existed, existing algorithms can not perform well. In this paper, a new method based on relation of the partial interframe differences is proposed. It can eliminate the influence of the video movement. The experimental results have showed that the new method performs well both in recall and precision.

关键词： Gunshot detection systems Histograms Change detection algorithms Content based retrieval Computer science Multimedia computing Internet Computer aided instruction Software libraries Electronic commerce

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