| A survey on medical diagnosis of diabetes using machine learning techniques A Choudhury, D Gupta Recent Developments in Machine Learning and Data Analytics: IC3 2018, 67-78, 2019 | 124 | 2019 |
| Modelling and forecasting of COVID-19 spread using wavelet-coupled random vector functional link networks BB Hazarika, D Gupta Applied Soft Computing 96, 106626, 2020 | 106 | 2020 |
| Density-weighted support vector machines for binary class imbalance learning BB Hazarika, D Gupta Neural Computing and Applications 33 (9), 4243-4261, 2021 | 86 | 2021 |
| A fuzzy twin support vector machine based on information entropy for class imbalance learning D Gupta, B Richhariya, P Borah Neural Computing and Applications, 1-12, 2018 | 81 | 2018 |
| 1-Norm extreme learning machine for regression and multiclass classification using Newton method S Balasundaram, D Gupta Neurocomputing 128, 4-14, 2014 | 71 | 2014 |
| Facial expression recognition using iterative universum twin support vector machine B Richhariya, D Gupta Applied Soft Computing 76, 53-67, 2019 | 59 | 2019 |
| Robust regularized extreme learning machine with asymmetric Huber loss function D Gupta, BB Hazarika, M Berlin Neural Computing and Applications 32 (16), 12971-12998, 2020 | 56 | 2020 |
| Entropy based fuzzy least squares twin support vector machine for class imbalance learning D Gupta, B Richhariya Applied Intelligence 48 (11), 4212-4231, 2018 | 55 | 2018 |
| Artificial intelligence for suspended sediment load prediction: a review D Gupta, BB Hazarika, M Berlin, UM Sharma, K Mishra Environmental earth sciences 80 (9), 346, 2021 | 52 | 2021 |
| Financial time series forecasting using twin support vector regression D Gupta, M Pratama, Z Ma, J Li, M Prasad PloS one 14 (3), e0211402, 2019 | 51 | 2019 |
| On optimization based extreme learning machine in primal for regression and classification by functional iterative method S Balasundaram, D Gupta International Journal of Machine Learning and Cybernetics 7, 707-728, 2016 | 50 | 2016 |
| Modeling suspended sediment load in a river using extreme learning machine and twin support vector regression with wavelet conjunction BB Hazarika, D Gupta, M Berlin Environmental Earth Sciences 79 (10), 234, 2020 | 47 | 2020 |
| Training Lagrangian twin support vector regression via unconstrained convex minimization S Balasundaram, D Gupta Knowledge-Based Systems 59, 85-96, 2014 | 47 | 2014 |
| Lagrangian support vector regression via unconstrained convex minimization S Balasundaram, D Gupta Neural networks 51, 67-79, 2014 | 39 | 2014 |
| An improved regularization based Lagrangian asymmetric ν-twin support vector regression using pinball loss function U Gupta, D Gupta Applied Intelligence 49 (10), 3606-3627, 2019 | 36 | 2019 |
| Training primal K-nearest neighbor based weighted twin support vector regression via unconstrained convex minimization D Gupta Applied Intelligence 47 (3), 962-991, 2017 | 35 | 2017 |
| Robust twin bounded support vector machines for outliers and imbalanced data P Borah, D Gupta Applied Intelligence 51 (8), 5314-5343, 2021 | 34 | 2021 |
| On robust asymmetric Lagrangian ν-twin support vector regression using pinball loss function D Gupta, U Gupta Applied Soft Computing 102, 107099, 2021 | 34 | 2021 |
| Computational approach to clinical diagnosis of diabetes disease: a comparative study D Gupta, A Choudhury, U Gupta, P Singh, M Prasad Multimedia Tools and Applications, 1-26, 2021 | 34 | 2021 |
| Universum based Lagrangian twin bounded support vector machine to classify EEG signals B Kumar, D Gupta Computer methods and programs in biomedicine 208, 106244, 2021 | 32 | 2021 |
Dr Barenya Bikash HazarikaAssistant ProfessorVerified email at adtu.in
