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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics
Rakesh Kumar Yadav
Indian Institute of Information Technology-Allahbad
Computer Science & IT Electrical & Electronics Engineering

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A Third Order based Additional Regularization in Intrinsic Space of the Manifold Rakesh Kumar Yadav; Abhishek Singh; Shekhar Verma; S. Venkatesan; M. Syafrullah; Krisna Adiyarta
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1961

Abstract

Second order graph Laplacian regularization has the limitation that the solution remains biased towards a constant which restricts its extrapolationcapability. The lack of extrapolation results in poor generalization. An additional penalty factor is needed on the function to avoid its over-fitting on seen unlabeled training instances. The third order derivative based technique identifies the sharp variations in the function and accurately penalizes them to avoid overfitting. The resultant function leads to a more accurate and generic model that exploits the twist and curvature variations on the manifold. Extensive experiments on synthetic and real-world data set clearly shows thatthe additional regularization increases accuracy and generic nature of model.
Co-Authors Abhishek Singh Krisna Adiyarta Mohammad Syafrullah S. Venkatesan Shekhar Verma