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ORCIDRupaj Kumar Nayak
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2020 – today
- 2021
[j7]Nirmalya Kumar Mohanty, Rupaj Kumar Nayak
:
A survey on update parameters of nonlinear conjugate gradient methods. Int. J. Math. Model. Numer. Optimisation 11(3): 292-325 (2021)- [i2]Yash Pratyush Sinha, Pranshu Malviya, Rupaj Kumar Nayak:
Fast constraint satisfaction problem and learning-based algorithm for solving Minesweeper. CoRR abs/2105.04120 (2021) - [i1]V. N. Aditya Datta Chivukula, Rupaj Kumar Nayak:
The impact of the additional features on the performance of regression analysis: a case study on regression analysis of music signal. CoRR abs/2105.05938 (2021) - 2020
- [j6]Nirmalya Kumar Mohanty, Rupaj Kumar Nayak:
A new efficient hybrid conjugate gradient method based on LS-DY-HS conjugate gradient parameter. Int. J. Math. Model. Numer. Optimisation 10(4): 342-364 (2020) - [j5]Rupaj Kumar Nayak, Nirmalya Kumar Mohanty:
Solution of boolean quadratic programming problems by two augmented Lagrangian algorithms based on a continuous relaxation. J. Comb. Optim. 39(3): 792-825 (2020)
2010 – 2019
- 2019
- [j4]Rupaj Kumar Nayak, Nirmalya Kumar Mohanty:
Improved row-by-row method for binary quadratic optimization problems. Ann. Oper. Res. 275(2): 587-605 (2019) - 2018
- [j3]Rupaj Kumar Nayak, Mahendra Prasad Biswal:
A low complexity semidefinite relaxation for large-scale MIMO detection. J. Comb. Optim. 35(2): 473-492 (2018) - 2016
- [j2]Rupaj Kumar Nayak, Jitamitra Desai:
A modified homogeneous potential reduction algorithm for solving the monotone semidefinite linear complementarity problem. Optim. Lett. 10(7): 1417-1448 (2016) - 2010
- [j1]Rupaj Kumar Nayak, Mahendra Prasad Biswal, S. Padhy:
Modification of Karmarkar's projective scaling algorithm. Appl. Math. Comput. 216(1): 227-235 (2010)
Coauthor Index
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