Object-Oriented Data Modelling for Graphics Databases: a Declarative Approach. - Neelam Bhalla; S. Balasundaram (Comput. Graph. Forum, 1991)

Operations and queries in object-oriented databases supporting complex objects. - Neelam Bhalla; S. Balasundaram (Inf. Softw. Technol., 1993)

Agent Based Suspect Stalking in Ad Hoc Wireless Networks. - Gautham V. Pallapa; S. Balasundaram (IICAI, 2003)

On Lagrangian support vector regression. - S. Balasundaram; Kapil 001 (Expert Syst. Appl., 2010)

On finite Newton method for support vector regression. - S. Balasundaram; Rampal Singh (Neural Comput. Appl., 2010)

Weighted fuzzy ridge regression analysis with crisp inputs and triangular fuzzy outputs. - S. Balasundaram; Kapil 001 (Int. J. Adv. Intell. Paradigms, 2011)

Application of error minimized extreme learning machine for simultaneous learning of a function and its derivatives. - S. Balasundaram; Kapil 001 (Neurocomputing, 2011)

Finite Newton method for implicit Lagrangian support vector regression. - S. Balasundaram; Kapil 001 (Int. J. Knowl. Based Intell. Eng. Syst., 2011)

On proximal bilateral-weighted fuzzy support vector machine classifiers. - S. Balasundaram; Muhammad Tanveer 001 (Int. J. Adv. Intell. Paradigms, 2012)

Smooth Newton method for implicit Lagrangian twin support vector regression. - S. Balasundaram; Muhammad Tanveer 001 (Int. J. Knowl. Based Intell. Eng. Syst., 2013)

On extreme learning machine for ε-insensitive regression in the primal by Newton method. - S. Balasundaram; Kapil 001 (Neural Comput. Appl., 2013)

On Lagrangian twin support vector regression. - S. Balasundaram; Muhammad Tanveer 001 (Neural Comput. Appl., 2013)

On implicit Lagrangian twin support vector regression by Newton method. - S. Balasundaram; Deepak Gupta 004 (Int. J. Comput. Intell. Syst., 2014)

1-Norm extreme learning machine for regression and multiclass classification using Newton method. - S. Balasundaram; Deepak Gupta 004; Kapil 001 (Neurocomputing, 2014)

Training Lagrangian twin support vector regression via unconstrained convex minimization. - S. Balasundaram; Deepak Gupta 004 (Knowl. Based Syst., 2014)

Lagrangian support vector regression via unconstrained convex minimization. - S. Balasundaram; Deepak Gupta 004; Kapil 001 (Neural Networks, 2014)

Training primal twin support vector regression via unconstrained convex minimization. - S. Balasundaram; Yogendra Meena (Appl. Intell., 2016)

A new approach for training Lagrangian support vector regression. - S. Balasundaram; Yogendra Meena (Knowl. Inf. Syst., 2016)

On optimization based extreme learning machine in primal for regression and classification by functional iterative method. - S. Balasundaram; Deepak Gupta 004 (Int. J. Mach. Learn. Cybern., 2016)

Knowledge-based extreme learning machines. - S. Balasundaram; Deepak Gupta 004 (Neural Comput. Appl., 2016)

A new approach for training Lagrangian twin support vector machine via unconstrained convex minimization. - S. Balasundaram; Deepak Gupta 004; Subhash Chandra Prasad (Appl. Intell., 2017)

On robust twin support vector regression in primal using squared pinball loss. - P. Anagha; S. Balasundaram; Yogendra Meena (J. Intell. Fuzzy Syst., 2018)

On a new approach for Lagrangian support vector regression. - S. Balasundaram; Gagandeep Benipal (Neural Comput. Appl., 2018)

Robust Support Vector Regression in Primal with Asymmetric Huber Loss. - S. Balasundaram; Yogendra Meena (Neural Process. Lett., 2019)

On pairing Huber support vector regression. - S. Balasundaram; Subhash Chandra Prasad (Appl. Soft Comput., 2020)

Robust twin support vector regression based on Huber loss function. - S. Balasundaram; Subhash Chandra Prasad (Neural Comput. Appl., 2020)

On Lagrangian L2-norm pinball twin bounded support vector machine via unconstrained convex minimization. - Subhash Chandra Prasad; S. Balasundaram (Inf. Sci., 2021)

Robust Pinball Twin Bounded Support Vector Machine for Data Classification. - Subhash Chandra Prasad; P. Anagha; S. Balasundaram (Neural Process. Lett., 2023)

FLSVR: Solving Lagrangian Support Vector Regression Using Functional Iterative Method. - Yogendra Meena; P. Anagha; S. Balasundaram (Neural Process. Lett., 2025)