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Prathibhamol C. P.

Asst. Professor, School of Computing, Amritapuri

Qualification: B-Tech, M.Tech
prathibhamolcp@am.amrita.edu
Research Interest: Computer Graphics, Databases

Bio

Prathibhamol C. P. currently serves as an Assistant Professor (Senior Grade) at the School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri.

 

Publications

Journal Article

Year : 2022

Combinational Features with centrality measurements on GCN+LR classification of Adversarial Attacks in homogenous Graphs

Cite this Research Publication : Sai, Gutta Akshitha, Komma Naga Sai Likhitha, Maddi Pavan Kalyan, Perisetla Anjani Devi, and C. P. Prathibhamol. "Combinational Features with centrality measurements on GCN+ LR classification of Adversarial Attacks in homogenous Graphs." In Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing, pp. 573-581. 2022.
Publisher : ACM

Publisher : ACM

Conference Paper

Year : 2017

An efficient solution for multi-label classification problem using apriori algorithm (MLC-A)

Cite this Research Publication :
S. Athira, Poojitha, K., and Prathibhamol CP, “An efficient solution for multi-label classification problem using apriori algorithm (MLC-A)”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017

Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Year : 2017

Prediction of cardiac arrhythmia type using clustering and regression approach (P-CA-CRA)

Cite this Research Publication : Prathibhamol CP, Suresh, A., and Suresh, G., “Prediction of cardiac arrhythmia type using clustering and regression approach (P-CA-CRA)”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017

Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Year : 2016

Multi label prediction using association rule generation and simple k-means

Cite this Research Publication : H. Haripriya, Prathibhamol CP, Pai, Y. R., Sandeep, M. S., Sankar, A. M., a, S. N. V., and Prof. Prema Nedungadi, “Multi label prediction using association rule generation and simple k-means”, in 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), 2016.

Publisher : 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT).

Year : 2016

Anomaly detection based multi label classification using Association Rule Mining (ADMLCAR)

Cite this Research Publication :
Prathibhamol CP, Amala, G. S., and Kapadia, M., “Anomaly detection based multi label classification using Association Rule Mining (ADMLCAR)”, in Second International Symposium on Emerging topics in Computing Communication, International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016

Publisher : Second International Symposium on Emerging topics in Computing Communication, International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Year : 2016

Multi label classification based on logistic regression (MLC-LR)

Cite this Research Publication : Prathibhamol CP, Jyothy, K. V., and Noora, B., “Multi label classification based on logistic regression (MLC-LR)”, in Second International Symposium on Emerging Topics in Computing and Communications, International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016

Publisher : Second International Symposium on Emerging Topics in Computing and Communications, International Conference on Advances in Computing, Communications and Informatics (ICACCI)

Conference Proceedings

Year : 2022

Comparative Study of Centrality based Adversarial Attacks on Graph Convolutional Network model for Node classification

Cite this Research Publication : Nair, Ankit B., Goutham Surendran, K. P. Prathyun, Vaishnav Sivaprasad, and C. P. Prathibhamol. "Comparative study of Centrality based Adversarial Attacks on Graph Convolutional Network model for Node classification." In 2022 7th International Conference on Communication and Electronics Systems (ICCES), pp. 731-736. IEEE, 2022.

Year : 2022

Comparative study of Centrality based Adversarial Attacks on Graph Convolutional Network model for Node classification

Cite this Research Publication : Nair, Ankit B., Goutham Surendran, K. P. Prathyun, Vaishnav Sivaprasad, and C. P. Prathibhamol. "Comparative study of Centrality based Adversarial Attacks on Graph Convolutional Network model for Node classification." In 2022 7th International Conference on Communication and Electronics Systems (ICCES), pp. 731-736. IEEE, 2022

Year : 2021

A Novel Approach Based on Associative Rule Mining Technique for Multi-label Classification (ARM-MLC)

Cite this Research Publication : Prathibhamol, C. P., K. Ananthakrishnan, Neeraj Nandan, Abhijith Venugopal, and Nandu Ravindran. "A novel approach based on associative rule mining technique for multi-label classification (ARM-MLC)." In Progress in Advanced Computing and Intelligent Engineering, pp. 195-203. Springer, Singapore, 2021.

Publisher : Springer

Year : 2021

Node Classification through Graph Embedding Techniques

Cite this Research Publication : Pranathi, Karedla Sai, and C. P. Prathibhamol. "Node Classification through Graph Embedding Techniques." In 2021 4th Biennial International Conference on Nascent Technologies in Engineering (ICNTE), pp. 1-4. IEEE, 2021.

Publisher : IEEE

Year : 2016

Solving multi label problems with clustering and nearest neighbor by consideration of labels

Cite this Research Publication :
Prathibhamol CP and Asha Ashok, “Solving multi label problems with clustering and nearest neighbor by consideration of labels”, 2nd International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS'15), Advances in Intelligent Systems and Computing, vol. 425. Springer , pp. 511-520, 2016.

Publisher : 2nd International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS'15), Advances in Intelligent Systems and Computing

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