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A family of maximum margin criterion for adaptive learning

Journal Article


Abstract


  • In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data samples, but either such characteristics or large data sets have become usual sense in real-world applications. In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D2 MMC, are designed to make adaptive learning applicable. Particularly, the MMC network is developed to learn deep features of images in light of simple deep networks. Experimental results on a diversity of data sets demonstrate the discriminant ability of proposed MMC methods are component to be adopted in complicated application scenarios.

UOW Authors


  •   Cheng, Miao (external author)
  •   Liu, Zunren (external author)
  •   Zou, Hongwei (external author)
  •   Tsoi, Ah Chung

Publication Date


  • 2018

Citation


  • Cheng, M., Liu, Z., Zou, H. & Tsoi, A. (2018). A family of maximum margin criterion for adaptive learning. Lecture Notes in Computer Science, 11303 375-387. 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13–16, 2018, Proceedings, Part III

Scopus Eid


  • 2-s2.0-85059003462

Number Of Pages


  • 12

Start Page


  • 375

End Page


  • 387

Volume


  • 11303

Place Of Publication


  • Germany

Abstract


  • In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data samples, but either such characteristics or large data sets have become usual sense in real-world applications. In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D2 MMC, are designed to make adaptive learning applicable. Particularly, the MMC network is developed to learn deep features of images in light of simple deep networks. Experimental results on a diversity of data sets demonstrate the discriminant ability of proposed MMC methods are component to be adopted in complicated application scenarios.

UOW Authors


  •   Cheng, Miao (external author)
  •   Liu, Zunren (external author)
  •   Zou, Hongwei (external author)
  •   Tsoi, Ah Chung

Publication Date


  • 2018

Citation


  • Cheng, M., Liu, Z., Zou, H. & Tsoi, A. (2018). A family of maximum margin criterion for adaptive learning. Lecture Notes in Computer Science, 11303 375-387. 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13–16, 2018, Proceedings, Part III

Scopus Eid


  • 2-s2.0-85059003462

Number Of Pages


  • 12

Start Page


  • 375

End Page


  • 387

Volume


  • 11303

Place Of Publication


  • Germany