S. Balasundaram

发表

Application of Extreme Learning Machine Method for Time Series Analysis

Ram Pal Singh, S. Balasundaram, S. Balasundaram, 2007 .

Smooth Newton method for implicit Lagrangian twin support vector regression

S. Balasundaram, Muhammad Tanveer, S. Balasundaram, 2013, Int. J. Knowl. Based Intell. Eng. Syst..

On implicit Lagrangian twin support vector regression by Newton method

S. Balasundaram, Deepak Gupta, S. Balasundaram, 2014, Int. J. Comput. Intell. Syst..

On robust twin support vector regression in primal using squared pinball loss

S. Balasundaram, P. Anagha, Yogendra Meena, 2018, J. Intell. Fuzzy Syst..

On a new approach for Lagrangian support vector regression

S. Balasundaram, Gagandeep Benipal, S. Balasundaram, 2018, Neural Computing and Applications.

Training primal twin support vector regression via unconstrained convex minimization

S. Balasundaram, Yogendra Meena, 2015, Applied Intelligence.

On proximal bilateral-weighted fuzzy support vector machine classifiers

S. Balasundaram, Muhammad Tanveer, 2012, Int. J. Adv. Intell. Paradigms.

On optimization based extreme learning machine in primal for regression and classification by functional iterative method

S. Balasundaram, Deepak Gupta, S. Balasundaram, 2016, Int. J. Mach. Learn. Cybern..

Weighted fuzzy ridge regression analysis with crisp inputs and triangular fuzzy outputs

S. Balasundaram, Kapil, 2011, Int. J. Adv. Intell. Paradigms.

A new approach for training Lagrangian support vector regression

S. Balasundaram, Yogendra Meena, S. Balasundaram, 2016, Knowledge and Information Systems.

On Lagrangian twin support vector regression

S. Balasundaram, Muhammad Tanveer, 2012, Neural Computing and Applications.

On Lagrangian support vector regression

S. Balasundaram, Kapil, S. Balasundaram, 2010, Expert Syst. Appl..

Object‐Oriented Data Modelling for Graphics Databases: a Declarative Approach

S. Balasundaram, Neelam Bhalla, S. Balasundaram, 1991, Comput. Graph. Forum.

Lagrangian support vector regression via unconstrained convex minimization

S. Balasundaram, Deepak Gupta, Kapil, 2014, Neural Networks.

Robust Support Vector Regression in Primal with Asymmetric Huber Loss

S. Balasundaram, Yogendra Meena, 2018, Neural Processing Letters.

Training Lagrangian twin support vector regression via unconstrained convex minimization

S. Balasundaram, Deepak Gupta, S. Balasundaram, 2014, Knowl. Based Syst..

1-Norm extreme learning machine for regression and multiclass classification using Newton method

S. Balasundaram, Deepak Gupta, Kapil, 2014, Neurocomputing.

Finite Newton method for implicit Lagrangian support vector regression

S. Balasundaram, Kapil, S. Balasundaram, 2011, Int. J. Knowl. Based Intell. Eng. Syst..

On extreme learning machine for ε-insensitive regression in the primal by Newton method

S. Balasundaram, Kapil, 2011, Neural Computing and Applications.

Agent Based Suspect Stalking in Ad Hoc Wireless Networks

S. Balasundaram, Gautham V. Pallapa, 2003, IICAI.

A new approach for training Lagrangian twin support vector machine via unconstrained convex minimization

S. Balasundaram, Deepak Gupta, Subhash Chandra Prasad, 2016, Applied Intelligence.

Knowledge-based extreme learning machines

S. Balasundaram, Deepak Gupta, 2015, Neural Computing and Applications.

On finite Newton method for support vector regression

S. Balasundaram, Rampal Singh, 2010, Neural Computing and Applications.

Operations and queries in object-oriented databases supporting complex objects

S. Balasundaram, Neelam Bhalla, S. Balasundaram, 1993, Inf. Softw. Technol..

Application of error minimized extreme learning machine for simultaneous learning of a function and its derivatives

S. Balasundaram, Kapil, S. Balasundaram, 2011, Neurocomputing.

Development of Micro Aerial Vehicle using Piezoelectric Fiber Composites

S. Balasundaram, 2013 .

On Lagrangian L2-norm pinball twin bounded support vector machine via unconstrained convex minimization

S. Balasundaram, Subhash Chandra Prasad, S. Balasundaram, 2021, Inf. Sci..

On existence of solution of the Dirichlet problem of fourth order partial differential equations with variable coefficients

S. Balasundaram, S. Balasundaram, P. K. Bhattacharyya, 1983 .

ON A MIXED-HYBRID FINITE ELEMENT METHOD FOR ANISOTROPIC PLATE BENDING PROBLEMS

S. Balasundaram, Neela Nataraj, S. Gopalsamy, 1996 .

Application of Lagrangian Twin Support Vector Machines for Classification

S. Balasundaram, S. Balasundaram, N. Kapil, 2010, 2010 Second International Conference on Machine Learning and Computing.

A mixed finite-element method for fourth-order elliptic problems with variable coefficients

S. Balasundaram, P. K. Bhattacharyya, 1988 .