S. Balasundaram

29 papers Journal 28Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
FLSVR: Solving Lagrangian Support Vector Regression Using Functional Iterative Method.
Neural Process. Lett.
Yogendra Meena, P. Anagha, S. Balasundaram
2023 J jnl
Robust Pinball Twin Bounded Support Vector Machine for Data Classification.
Neural Process. Lett.
Subhash Chandra Prasad, P. Anagha, S. Balasundaram
2021 J jnl
On Lagrangian L2-norm pinball twin bounded support vector machine via unconstrained convex minimization.
Inf. Sci.
Subhash Chandra Prasad, S. Balasundaram
2020 J jnl
On pairing Huber support vector regression.
Appl. Soft Comput.
S. Balasundaram, Subhash Chandra Prasad
2020 J jnl
Robust twin support vector regression based on Huber loss function.
Neural Comput. Appl.
S. Balasundaram, Subhash Chandra Prasad
2019 J jnl
Robust Support Vector Regression in Primal with Asymmetric Huber Loss.
Neural Process. Lett.
S. Balasundaram, Yogendra Meena
2018 J jnl
On a new approach for Lagrangian support vector regression.
Neural Comput. Appl.
S. Balasundaram, Gagandeep Benipal
2018 J jnl
On robust twin support vector regression in primal using squared pinball loss.
J. Intell. Fuzzy Syst.
P. Anagha, S. Balasundaram, Yogendra Meena
2017 J jnl
A new approach for training Lagrangian twin support vector machine via unconstrained convex minimization.
Appl. Intell.
S. Balasundaram, Deepak Gupta, Subhash Chandra Prasad
2016 J jnl
A new approach for training Lagrangian support vector regression.
Knowl. Inf. Syst.
S. Balasundaram, Yogendra Meena
2016 J jnl
Knowledge-based extreme learning machines.
Neural Comput. Appl.
S. Balasundaram, Deepak Gupta
2016 J jnl
On optimization based extreme learning machine in primal for regression and classification by functional iterative method.
Int. J. Mach. Learn. Cybern.
S. Balasundaram, Deepak Gupta
2016 J jnl
Training primal twin support vector regression via unconstrained convex minimization.
Appl. Intell.
S. Balasundaram, Yogendra Meena
2014 J jnl
1-Norm extreme learning machine for regression and multiclass classification using Newton method.
Neurocomputing
S. Balasundaram, Deepak Gupta, Kapil
2014 J jnl
Lagrangian support vector regression via unconstrained convex minimization.
Neural Networks
S. Balasundaram, Deepak Gupta, Kapil
2014 J jnl
On implicit Lagrangian twin support vector regression by Newton method.
Int. J. Comput. Intell. Syst.
S. Balasundaram, Deepak Gupta
2014 J jnl
Training Lagrangian twin support vector regression via unconstrained convex minimization.
Knowl. Based Syst.
S. Balasundaram, Deepak Gupta
2013 J jnl
On Lagrangian twin support vector regression.
Neural Comput. Appl.
S. Balasundaram, Muhammad Tanveer
2013 J jnl
On extreme learning machine for ε-insensitive regression in the primal by Newton method.
Neural Comput. Appl.
S. Balasundaram, Kapil
2013 J jnl
Smooth Newton method for implicit Lagrangian twin support vector regression.
Int. J. Knowl. Based Intell. Eng. Syst.
S. Balasundaram, Muhammad Tanveer
2012 J jnl
On proximal bilateral-weighted fuzzy support vector machine classifiers.
Int. J. Adv. Intell. Paradigms
S. Balasundaram, Muhammad Tanveer
2011 J jnl
Application of error minimized extreme learning machine for simultaneous learning of a function and its derivatives.
Neurocomputing
S. Balasundaram, Kapil
2011 J jnl
Finite Newton method for implicit Lagrangian support vector regression.
Int. J. Knowl. Based Intell. Eng. Syst.
S. Balasundaram, Kapil
2011 J jnl
Weighted fuzzy ridge regression analysis with crisp inputs and triangular fuzzy outputs.
Int. J. Adv. Intell. Paradigms
S. Balasundaram, Kapil
2010 J jnl
On Lagrangian support vector regression.
Expert Syst. Appl.
S. Balasundaram, Kapil
2010 J jnl
On finite Newton method for support vector regression.
Neural Comput. Appl.
S. Balasundaram, Rampal Singh
2003 — conf
Agent Based Suspect Stalking in Ad Hoc Wireless Networks.
IICAI
Gautham V. Pallapa, S. Balasundaram
1993 J jnl
Operations and queries in object-oriented databases supporting complex objects.
Inf. Softw. Technol.
Neelam Bhalla, S. Balasundaram
1991 J jnl
Object-Oriented Data Modelling for Graphics Databases: a Declarative Approach.
Comput. Graph. Forum
Neelam Bhalla, S. Balasundaram