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  1. Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance

    The chapter introduces the latest developments and results of Iterative Single Data Algorithm (ISDA) for solving large-scale support vector machines...
    V. Kecman, T.-M. Huang, M. Vogt in Support Vector Machines: Theory and Applications
    Chapter

  2. Support Vector Machines – An Introduction

    This is a book about learning from empirical data (i.e., examples, samples, measurements, records, patterns or observations) by applying support...
    V. Kecman in Support Vector Machines: Theory and Applications
    Chapter

  3. Cancer Diagnosis and Protein Secondary Structure Prediction Using Support Vector Machines

    In this chapter, we use support vector machines (SVMs) to deal with two bioinformatics problems, i.e., cancer diagnosis based on gene expression data...
    F. Chu, G. **, L. Wang in Support Vector Machines: Theory and Applications
    Chapter

  4. Collision Free Motion Planning on Graphs

    A topological theory initiated in [4,5] uses methods of algebraic topology to estimate numerically the character of instabilities arising in motion...
    Michael Farber in Algorithmic Foundations of Robotics VI
    Chapter

  5. Coordinating Multiple Droplets in Planar Array Digital Microfluidics System

    This paper presents an approach to coordinate the motions of droplets in digital microfluidic systems used for biochemical analysis. A digital...
    Eric Griffith, Srinivas Akella in Algorithmic Foundations of Robotics VI
    Chapter

  6. Multi View and Multi Scale Image Based Visual Servo For Micromanipulation

    In this article, we present vision-based techniques for solving some of the problems of micromanipulation. Manipulation and assembly at the micro...
    Rajagoplalan Devanathan, Sun Wenting, ... An-drew Shacklock in Innovations in Robot Mobility and Control
    Chapter

  7. From Classical Connectionist Models to Probabilistic/Generalised Regression Neural Networks (PNNs/GRNNs)

    This chapter begins by briefly summarising some of the well-known classical connectionist/artificial neural network models such as multi-layered...
    Tetsuya Hoya in Artificial Mind System - Kernel Memory Approach
    Chapter

  8. Sequential Pattern Mining*

    Sequential pattern discovery has emerged as an important research topic in knowledge discovery and data mining with broad applications. Previous...
    Tian-Rui Li, Yang Xu, ... Wu-ming Pan in Intelligent Data Mining
    Chapter

  9. Discovering the Factors Affecting the Location Selection of FDI in China*

    Since the late 1970s, Foreign Direct Investment (FDI) has played an important role in the economic development of China. However, the growth of FDI...
    Li Zhang, Yujie Zhu, ... Guoqing Chen in Intelligent Data Mining
    Chapter

  10. Data Mining and User Profiling for an E-Commerce System

    Many companies are now develo** an online internet presence to sell or promote their products and services. The data generated by e-commerce sites...
    Ken McGarry, Andrew Martin, Dale Addison in Classification and Clustering for Knowledge Discovery
    Chapter

  11. Ontology-based Fuzzy Decision Agent and Its Application to Meeting Scheduling Support System

    A Fuzzy Decision Agent (FDA) based on personal ontology for Meeting Scheduling Support System (MSSS) is proposed in this chapter. In this system,...
    Chang-Shing Lee, Hei-Chia Wang, Meng-Ju Chang in Classification and Clustering for Knowledge Discovery
    Chapter

  12. D-GridMST: Clustering Large Distributed Spatial Databases

    In this paper, we will propose a novel distributable clustering algorithm, called Distributed-GridMST (D–GridMST for short), which deals with large...
    Ji Zhang, Han Liu in Classification and Clustering for Knowledge Discovery
    Chapter

  13. A Probabilistic Approach to Mining Fuzzy Frequent Patterns

    Deriving association rules is a typical task in data mining. The problem was originally defined for transactions of discrete items, but it was soon...
    Attila Gyenesei, Jukka Teuhola in Classification and Clustering for Knowledge Discovery
    Chapter

  14. Data Mining of Missing Persons Data

    This paper presents the results of analysis to evaluate the effectiveness of data mining techniques to predict the outcome for missing persons cases....
    K. Blackmore, T. Bossomaier, ... D. Thomson in Classification and Clustering for Knowledge Discovery
    Chapter

  15. 6 Beamforming Combined with Multi-channel Acoustic Echo Cancellation

    For audio signal acquisition, beamforming microphone arrays can be efficiently used for enhancing a desired signal while suppressing...
    Wolfgang Herbordt in Sound Capture for Human/Machine Interfaces
    Chapter

  16. 4 Optimum Beamforming for Wideband Non-stationary Signals

    Array processing techniques strive for extraction of maximum information from a propagating wave field using groups of sensors, which are located at...
    Wolfgang Herbordt in Sound Capture for Human/Machine Interfaces
    Chapter

  17. Linkage Learning Genetic Algorithm

    In order to handle linkage evolution and to tackle the ordering problem, Harik [47] took Holland’s call [53] for the evolution of tight linkage quite...
    Ying-** Chen in Extending the Scalability of Linkage Learning Genetic Algorithms
    Chapter

  18. Preliminaries: Assumptions and the Test Problem

    After introducing the background and motivation of the linkage learning genetic algorithm, we will start to improve and understand the linkage...
    Ying-** Chen in Extending the Scalability of Linkage Learning Genetic Algorithms
    Chapter

  19. Modeling of Fuzzy Data

    Fuzzy data are imprecise data obtained from measurements, perception or by interviewing people. Typically, those data are expressed in linguistic...
    Hung T. Nguyen, Berlin Wu in Fundamentals of Statistics with Fuzzy Data
    Chapter

  20. Data Driven Fuzzy Modelling with Neural Networks

    Extraction of models for complex systems from numerical data of behavior is studied. In particular, systems representable as sets of fuzzy if-then...
    C. Moraga in Real World Applications of Computational Intelligence
    Chapter
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