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Machine Learning and Cybernetics

13th International Conference, Lanzhou, China, July 13-16, 2014. Proceedings

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Xizhao Wang

    1. Hebei University, Baoding, China

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  2. Witold Pedrycz

    1. Department of Electrical and Computer En, University of Alberta, Edmonton, Canada

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  3. Patrick Chan

    1. South China University of Technology, Guangzhou, China

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  4. Qiang He

    1. Hebei University, Baoding, China

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  • Fast-track conference proceedings
  • State-of-the-art research
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  • Includes supplementary material: sn.pub/extras

Part of the book series: Communications in Computer and Information Science (CCIS, volume 481)

Included in the following conference series:

Conference proceedings info: ICMLC 2014.

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Table of contents (45 papers)

  1. Front Matter

    Pages I-XIV
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  2. Classification and Semi-Supervised Learning

    1. Front Matter

      Pages 1-1
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    2. Combining Classifiers Based on Gaussian Mixture Model Approach to Ensemble Data

      • Tien Thanh Nguyen, Alan Wee-Chung Liew, Minh Toan Tran, Mai Phuong Nguyen
      Pages 3-12

    3. Sentiment Classification of Chinese Reviews in Different Domain: A Comparative Study

      • Qingqing Zhou, Chengzhi Zhang
      Pages 13-23

    4. A Computer-Aided System for Classification of Breast Tumors in Ultrasound Images via Biclustering Learning

      • Qiangzhi Zhang, Huali Chang, Longzhong Liu, Anhua Li, Qinghua Huang
      Pages 24-32

    5. An Improved Approach to Ordinal Classification

      • Donghui Wang, Junhai Zhai, Hong Zhu, Xizhao Wang
      Pages 33-42

    6. Classification Based on Lower Integral and Extreme Learning Machine

      • Aixia Chen, Huimin Feng, Zhen Guo
      Pages 43-51

    7. User Input Classification for Chinese Question Answering System

      • Yongshuai Hou, Xiaolong Wang, Qingcai Chen, Man Li, Cong Tan
      Pages 52-59

    8. Fusion of Classifiers Based on a Novel 2-Stage Model

      • Tien Thanh Nguyen, Alan Wee-Chung Liew, Minh Toan Tran, Thi Thu Thuy Nguyen, Mai Phuong Nguyen
      Pages 60-68

  3. Clustering and Kernel

    1. Front Matter

      Pages 69-69
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    2. Comparative Analysis of Density Estimation Based Kernel Regression

      • Junying Chen, Yulin He
      Pages 71-79

    3. Thermal Power Units’ Energy Consuming Speciality Analysis Based on Support Vector Regression (SVR)

      • Ming Zhao, Zhengbo Yan, Liukun Zhou
      Pages 80-87

    4. Bandwidth Selection for Nadaraya-Watson Kernel Estimator Using Cross-Validation Based on Different Penalty Functions

      • Yumin Zhang
      Pages 88-96

    5. A Hough Transform-Based Biclustering Algorithm for Gene Expression Data

      • Cuong To, Tien Thanh Nguyen, Alan Wee-Chung Liew
      Pages 97-106

    6. An Effective Biclustering Algorithm for Time-Series Gene Expression Data

      • Huixin Xu, Yun Xue, Zhihao Lu, Xiaohui Hu, Hongya Zhao, Zhengling Liao et al.
      Pages 107-116

    7. Multiple Orthogonal K-means Hashing

      • Ziqian Zeng, Yueming Lv, Wing W. Y. Ng
      Pages 117-126

  4. Application to Recognition

    1. Front Matter

      Pages 127-127
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    2. Recognizing Bangladeshi Currency for Visually Impaired

      • Mohammad M. Rahman, Bruce Poon, M. Ashraful Amin, Hong Yan
      Pages 129-135

    3. Face Recognition Using Genetic Algorithm

      • Qin Qing, Eric C. C. Tsang
      Pages 136-143

    4. Face Liveness Detection by Brightness Difference

      • Patrick P. K. Chan, Ying Shu
      Pages 144-150
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Other volumes

  1. Machine Learning and Cybernetics

Keywords

About this book

This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Cybernetics, Lanzhou, China, in July 2014. The 45 revised full papers presented were carefully reviewed and selected from 421 submissions. The papers are organized in topical sections on classification and semi-supervised learning; clustering and kernel; application to recognition; sampling and big data; application to detection; decision tree learning; learning and adaptation; similarity and decision making; learning with uncertainty; improved learning algorithms and applications.

Editors and Affiliations

  • Hebei University, Baoding, China

    Xizhao Wang, Qiang He

  • Department of Electrical and Computer En, University of Alberta, Edmonton, Canada

    Witold Pedrycz

  • South China University of Technology, Guangzhou, China

    Patrick Chan

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