Sureshan Pareth
Date of Joining NITK:
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Academic Background:
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PhD. (NITK Surathkal, 2013)
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M.Tech (NITK Surathkal, 2001)
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MCA (1996)
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M.Sc (Mathematics, 1988)
Areas of Interest:
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Machine Learning
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Deep Learning
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Optimization Techniques
Publications:
Journal articles
1. Pareth, Suresan. "Neural-Enhanced Two-Step Modified Newton-Lavrentiev Method: A structure-preserving deep learning approach for Ill-posed inverse problems." Machine Learning with Applications (2025): 100761.
2. George, S., and Pareth, S. (2012). “Two-Step Modified Newton Method for Nonlinear Lavrentiev Regularization.”, International Scholarly Research Network (ISRN), Applied Mathematics, Volume 2012, Article ID 728627, doi:10.5402/2012/728627.
3. George, S., and Pareth, S. (2012). “An Application of Newton Type Iterative Method for Lavrentiev Regularization for Ill-Posed Equations: Finite Dimensional Realization”, IAENG International Journal of Applied Mathematics, 42:3, pp 164-170.
4. George, S., and Pareth, S. (2013). “An Application of Newton type Iterative Method for the Approximate Implementation of Lavrentiev Regularization”, Journal of Applied Analysis, De Gruyter, 19, pp 181-196.
5. George, S., Pareth, S. and Kunhanandan, M., (2013) “Newton Lavrentiev regularization for ill-posed operator equationsin Hilbert scales”, Applied Mathematics and Computation, Elsevier . Volume 219, Issue 24, pp 11191–11197.
Conference articles
1. Pareth, S., and George, S. (2012). “Projection Scheme for Newton-type Iterative Method for Lavrentiev Regularization", Mathew et. al. (Eds.): ICECCS 2012, CCIS 305, pp. 302310, ©Springer-Verlag Berlin Heidelberg.
2. Pareth, S. “Finite Dimensional Realization of Lavrentiev Regularization for Nonlinear Illposed Equations", International conference ICERECT 2012 ,©Springer-Verlag Emerging Research in Electronics, Computer Science and Technology, Lecture Notes in Electrical Engineering Volume 248, 2014, pp 87-98.
3. Pareth, S., “Gauss-Newton Regularization Method for Signal Reconstruction”, ( International Conference on Computing, Communications, and Information Science published in proceedings by Elsevier India).