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Balasundaram, S.
470  Ergebnisse:
Personensuche X
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1

Development and Analysis of Novel IoT based Monitoring Syst..:

, In: 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN),
Prashanth, S. ; Balasundaram, S. ; Hariharan, S.B.. - p. 1352-1359 , 2023
Link: https://doi.org/10.1109/..
 
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2

Integrating IoT and Sensor Technology for Improved Industri..:

, In: 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN),
Balasundaram, S. ; Prabhu, S. ; Kumar R, Gowsik Surya. - p. 1381-1386 , 2023
Link: https://doi.org/10.1109/..
 
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3

Enabling IP/optical integration in core and metro networks:

, In: 49th European Conference on Optical Communications (ECOC 2023),
Lopez, V. ; Landon, P. ; Balasundaram, S.. - p. None , 2023
Link: https://doi.org/10.1049/..
 
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4

Outcomes of abo-incompatible kidney transplantation: Novel ..:

Pathak, Vivek ; Venkatesan, Madhav ; Madhavan, Devdas...
Transplantation Reports.  8 (2023)  2 - p. 100127 , 2023
Link: https://doi.org/10.1016/..
 
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5

Robust Pinball Twin Bounded Support Vector Machine for Data..:

Prasad, Subhash Chandra ; Anagha, P. ; Balasundaram, S.
Neural Processing Letters.  55 (2022)  2 - p. 1131-1153 , 2022
Link: https://doi.org/10.1007/..
 
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6

On Twin Bounded Support Vector Machine with Pinball Loss:

, In: Lecture Notes in Electrical Engineering; Advanced Machine Intelligence and Signal Processing,
Anagha, P. ; Balasundaram, S. - p. 177-190 , 2022
Link: https://doi.org/10.1007/..
 
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7

On Lagrangian L2-norm pinball twin bounded support vector m..:

Prasad, Subhash Chandra ; Balasundaram, S.
Information Sciences.  571 (2021)  - p. 279-302 , 2021
Link: https://doi.org/10.1016/..
 
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8

On pairing Huber support vector regression:

Balasundaram, S. ; Prasad, Subhash Chandra
Applied Soft Computing.  97 (2020)  - p. 106708 , 2020
Link: https://doi.org/10.1016/..
 
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9

Theoretical background, first stage development and adaptat..:

Tay, A. K. ; Miah, M. A. A. ; Khan, S....
Epidemiology and Psychiatric Sciences.  29 (2019)  - p. , 2019
Link: https://doi.org/10.1017/..
 
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10

Robust twin support vector regression based on Huber loss f..:

Balasundaram, S. ; Prasad, Subhash Chandra
Neural Computing and Applications.  32 (2019)  15 - p. 11285-11309 , 2019
Link: https://doi.org/10.1007/..
 
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11

L1-Norm Support Vector Regression in Primal Based on Huber ..:

, In: Proceedings of ICETIT 2019; Lecture Notes in Electrical Engineering,
Puthiyottil, Anagha ; Balasundaram, S. ; Meena, Yogendra - p. 195-205 , 2019
Link: https://doi.org/10.1007/..
 
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12

Robust Support Vector Regression in Primal with Asymmetric ..:

Balasundaram, S. ; Meena, Yogendra
Neural Processing Letters.  49 (2018)  3 - p. 1399-1431 , 2018
Link: https://doi.org/10.1007/..
 
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13

A new approach for training Lagrangian twin support vector ..:

Balasundaram, S. ; Gupta, Deepak ; Prasad, Subhash Chandra
Applied Intelligence.  46 (2016)  1 - p. 124-134 , 2016
Link: https://doi.org/10.1007/..
 
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14

On a new approach for Lagrangian support vector regression:

Balasundaram, S. ; Benipal, Gagandeep
Neural Computing and Applications.  29 (2016)  9 - p. 533-551 , 2016
Link: https://doi.org/10.1007/..
 
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15

A new approach for training Lagrangian support vector regre..:

Balasundaram, S. ; Meena, Yogendra
Knowledge and Information Systems.  49 (2016)  3 - p. 1097-1129 , 2016
Link: https://doi.org/10.1007/..
 
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