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Pritam Anand

Pritam Anand
Pritam Anand
 
PhD (Computer Science), South Asian University, New Delhi

Contact Details

 
079-68261657
 
# 3103, FB-3, DA-IICT, Gandhinagar, Gujarat, India – 382007
 
https://scholar.google.com/citations?user=ATYzQhoAAAAJ&hl=en

Biography

Pritam Anand is currently Assistant Professor at DAIICT. His research interest moves around the Support Vector Machine Algorithms. He has obtained his Master degree in Computer Science from South Asian University, New Delhi (An international university established by SAARC countries).  He has obtained his Ph.D. degree in Computer Science from South Asian University, New Delhi.  He was the recipient of the prestigious Visvesvaraya Ph.D. fellowship during his doctoral degree.

Specialization

Support Vector Machines, Loss Functions, Regression, Extreme Learning Machine, Quantile Regression

Publications

  • Pritam Anand, Reshma Rastogi and Suresh Chandra. A Class of New Support Vector Regression Models, Applied Soft Computing 94 (2020) 106446.
  • Pritam Anand, Reshma Rastogi and Suresh Chandra. A new asymmetric ε-insensitive pinball loss function based support vector quantile regression model, Applied Soft Computing 94 (2020) 106473.
  • Pritam Anand . Learning a powerful SVM using piece-wise linear loss functions, preprint at arXiv:2102.04849.
  • Pritam Anand, Reshma Rastogi and Suresh Chandra. Support Vector Regression via a Combined Reward Cum Penalty Loss Function preprint arXiv:1904.12331 (2019).
  • Pritam Anand, Reshma Rastogi and Suresh Chandra. A v-support vector quantile regression model with automatic accuracy control preprint arXiv:1910.09168 (2019).
  • Reshma Rastogi, Pritam Anand and Suresh Chandra. Large-margin Distribution Machine-based regression, Neural Computing & Applications 32(8) (2020):3633-3648.
  • Reshma Rastogi, Pritam Anand and Suresh Chandra. A v-twin support vector machine based regression with automatic accuracy control, Applied Intelligence 46(3) (2017):670-689.
  • Reshma Rastogi, Pritam Anand and Suresh Chandra. L1-norm Twin Support Vector Machine-based Regression, Optimization 66(11) (2017):1895-1911.
  • Mohmad Tanveer, Shipa Shama, Reshma Rastogi and Pritam Anand.Sparse Support Vector machine with pinball loss. Transactions on Emerging Telecommunications Technologies (ETT) (2020) e3820.
  • Srinivas Rao , AR Pais and Pritam Anand . A heuristic technique to detect phishing websites using TWSVM classifier. Neural Computation & Application (2020), https://doi.org/10.1007/s00521-020-05354-z.

Teaching

Probability and Statistics

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