个人简历

研究领域

My Research Interests Machine Learning, Artificial Intelligence, fuzzy sets theory, neural networks, evolutionary computation, bioinformatics, and brain science.""

近期论文

1.Huaqin Zhang, Jian Wang, Zhanquan Sun, Jacek M. Zurada, and Nikhil R. Pal, Feature Selection for Neural Networks Using Group Lasso Regularization, IEEE Transactions on Knowledge and Data Engineering, 2019, to appear \r
2. Hao Zhang, Nikhil R. Pal, Yin Sheng, and Zhigang Zeng, Distributed Adaptive Tracking Synchronization for Coupled Reaction-Diffusion Neural Network IEEE Transactions on Neural Networks and Learning Systems Accepted. \r
3. Jian Wang, Qingquan Chang, Qin Chang, Yusong Liu and Nikhil R. Pal, Weight noise injectionbased MLPs with group lasso penalty: Asymptotic Convergence and application to node pruning, IEEE Transactions on Cybernetics, 2018, to appear. \r
4. Tao Gao, Jian Wang, Bingjie Zhang, Huaqing Zhang, Peng Ren, and Nikhil R. Pal, A PolakRibie`re-Polyak conjugate gradient-based neuro-fuzzy network and its convergence, IEEE Access, Vol. 7, pp 41551 - 41565, 2018, DOI: 10.1109/ACCESS.2018.2848117. \r
5. Kaustuv Nag, Tandra Pal, Rajani K. Mudi, and Nikhil R. Pal, Robust Multiobjective Optimization with Robust Consensus, IEEE Trans. on Fuzzy Systems, 2018, DOI: 10.1109/TFUZZ.2018.2848261. \r
6. Ignacio Montes, Nikhil R. Pal, and Susana Montes, Entropy Measures for Atanassov intuitionistic fuzzy sets based on divergence, Soft Computing, August 2018, Volume 22, Issue 15, pp 50515071, DOI https://doi.org/10.1007/s00500-018-3318-3 \r
7. Bikram Karmakar, Nikhil R Pal, How to make a neural network say Dont know. Information Sciences.Vol 430-431, pp 444-466, March 2018 \r
8. R. Panja and N. R. Pal, MS-SVM: Minimally Spanned Support Vector Machine, Applied soft Computing, DOI 10.1016/j.asoc.2017.12.017, Vol 64; pp 356-365 March 2018. \r
9. C-T Lin, T-Y Hsieh, Y-T Liu,Y-Y Lin, C-N Fang, Y-K Wang, G Yen, N. R. Pal, C-H Chuang, Minority Oversampling in Kernel Adaptive Subspaces for Class Imbalanced Datasets, IEEE Trans. on Knowledge and Data Engineering, DOI 10.1109/TKDE.2017.2779849, Nov 2017. \r
10. Liu, Yu-Ting, Nikhil R. Pal, Amar R. Marathe, Yu-Kai Wang, and Chin-Teng Lin. ”Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources.” Frontiers in neuroscience, \r
11 (332), DOI: https://doi.org/10.3389/fnins.2017.00332, 2017. 11. G. Ochoa, I. Lizasoain, D. Paternain, H. Bustince, and Nikhil R Pal, From quantitative to qualitative orness for Lattice OWA operators, International Journal of General Systems, doi:10.1080/03081079.2017.1319364, Vol. 46(6), pp 640-669, 2017. \r
12. Chung, I-Fang, Yi-Cheng Chen, and Nikhil Pal. ”Feature selection with controlled redundancy in a fuzzy rule based framework.” IEEE Transactions on Fuzzy Systems, 10.1109/TFUZZ.2017.2688358, March 2017. \r
13. P. Dey, K. Nag, T. Pal, and Nikhil R. Pal,Regularizing Multi-Layer Perceptron for Robustness, IEEE Trans. on Systems, Man, and Cybernetics: Systems, 10.1109/TSMC.2017.2664143, February 2017. \r
14. Yu-Ting Liu, Nikhil R. Pal, Shang-Lin Wu, Amar Marathe and Chin-Teng Lin, Weighted Fuzzy Dempster-Shafer Framework for Multi-Modal Information Integration, IEEE Transactions on Fuzzy Systems, DOI 10.1109/TFUZZ.2017.2659764, January 2017. \r
15. Prantik Chatterjee and Nikhil R. Pal, Construction of synergy networks from gene expression data related to disease, GENE, May 21, 2016. doi: 10.1016/j.gene.2016.05.029. \r
16. A. Pathak and Nikhil R. Pal,Clustering of mixed data by integrating fuzzy, probabilistic and collaborative clustering framework, International Journal of Fuzzy Systems, 2016, 10.1007/s40815- 016-0168-y \r
17. Prantik Chatterjee, and Nikhil R. Pal, Discovery of synergistic genetic network: a minimum spanning tree-based approach. Journal of bioinformatics and computational biology, Vol. 14 (1), 2016, pp 1650003-19, DOI: 10.1142/S0219720016500037. \r
18. K. Sarkar, P. Chatterjee and Nikhil R. Pal, Finding synergy networks from gene expression data: a fuzzy rule based approach, IEEE Transactions on Fuzzy systems, DOI 10.1109/TFUZZ.2016.2540062, 2016 \r
19. P. Singh, Nikhil R. Pal,S Verma, and O P Vyas, Fuzzy Rule-Based Approach for Software Fault Prediction, IEEE Transactions on Systems, Man and Cybernetics: Systems, 2DOI 10.1109/TSMC.2016.2521840, 2015 \r
20. C-S Huang,Nikhil R. Pal,C-H Chuang,and C-T Lin, Identifying Changes in EEG Information Transfer during Drowsy Driving by Transfer Entropy, Frontiers in Human Neuroscience, 2015, DOI: 10.3389/fnhum.2015.00570; October 2015, .