Adil M. Bagirov

Adil M. Bagirov, Julien Ugon, Hijran Mirzayeva: Nonsmooth nonconvex optimization approach to clusterwise linear regression problems. European Journal of Operational Research 229(1): 132-142 (2013)

Adil M. Bagirov, L. Jin, N. Karmitsa, A. Al Nuaimat, Napsu Sultanova: Subgradient Method for Nonconvex Nonsmooth Optimization. J. Optimization Theory and Applications 157(2): 416-435 (2013)

Adil M. Bagirov, A. F. Barton, H. Mala-Jetmarova, A. Al Nuaimat, S. T. Ahmed, Napsu Sultanova, John Yearwood: An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling. Mathematical and Computer Modelling 57(3-4): 873-886 (2013)

N. M. S. Karmitsa, Adil M. Bagirov, Marko M. Mäkelä: Comparing different nonsmooth minimization methods and software. Optimization Methods and Software 27(1): 131-153 (2012)

Adil M. Bagirov, Julien Ugon, Dean Webb: An efficient algorithm for the incremental construction of a piecewise linear classifier. Inf. Syst. 36(4): 782-790 (2011)

Adil M. Bagirov, Julien Ugon: Codifferential method for minimizing nonsmooth DC functions. J. Global Optimization 50(1): 3-22 (2011)

Adil M. Bagirov, Julien Ugon, Dean Webb, B. Karasözen: Classification through incremental max-min separability. Pattern Anal. Appl. 14(2): 165-174 (2011)

Adil M. Bagirov, Julien Ugon, Dean Webb: Fast modified global k-means algorithm for incremental cluster construction. Pattern Recognition 44(4): 866-876 (2011)

Adil M. Bagirov, Conny Clausen, Michael Kohler: An algorithm for the estimation of a regression function by continuous piecewise linear functions. Comp. Opt. and Appl. 45(1): 159-179 (2010)

Adil M. Bagirov, Asef Nazari Ganjehlou: A quasisecant method for minimizing nonsmooth functions. Optimization Methods and Software 25(1): 3-18 (2010)

Adil M. Bagirov, Conny Clausen, Michael Kohler: An L2-boosting algorithm for estimation of a regression function. IEEE Transactions on Information Theory 56(3): 1417-1429 (2010)

Adil M. Bagirov, Conny Clausen, Michael Kohler: Estimation of a Regression Function by Maxima of Minima of Linear Functions. IEEE Transactions on Information Theory 55(2): 833-845 (2009)

Adil M. Bagirov: Continuous Approximations to Subdifferentials. Encyclopedia of Optimization 2009: 475-482

Adil M. Bagirov: Derivative-Free Methods for Non-smooth Optimization. Encyclopedia of Optimization 2009: 648-655

Adil M. Bagirov, Gleb Beliakov: Global Optimization: Cutting Angle Method. Encyclopedia of Optimization 2009: 1304-1311

Adil M. Bagirov: Nonsmooth Optimization Approach to Clustering. Encyclopedia of Optimization 2009: 2664-2671

Adil M. Bagirov, Asef Nazari Ganjehlou: An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization. Math. Meth. of OR 67(2): 187-206 (2008)

Adil M. Bagirov: Modified global k. Pattern Recognition 41(10): 3192-3199 (2008)

Sol Hart, John Yearwood, Adil M. Bagirov: Visual Tools for Analysing Evolution, Emergence, and Error in Data Streams. ACIS-ICIS 2007: 987-992

Adil M. Bagirov, John Yearwood: A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems. European Journal of Operational Research 170(2): 578-596 (2006)

Ranadhir Ghosh, John Yearwood, Moumita Ghosh, Adil M. Bagirov: A Hybrid Neural Learning Algorithm Using Evolutionary Learning and Derivative Free Local Search Method. Int. J. Neural Syst. 16(3): 201-214 (2006)

Ranadhir Ghosh, Moumita Ghosh, Adil M. Bagirov: Derivative Free Stochastic Discrete Gradient Method with Adaptive Mutation. Industrial Conference on Data Mining 2006: 264-278

Leonid Churilov, Adil M. Bagirov, Daniel Schwartz, Kate A. Smith, Michael Dally: Data Mining with Combined Use of Optimization Techniques and Self-Organizing Maps for Improving Risk Grouping Rules: Application to Prostate Cancer Patients. J. of Management Information Systems 21(4): 85-100 (2005)

Ranadhir Ghosh, John Yearwood, Moumita Ghosh, Adil M. Bagirov: Fusion Strategies for Neural Learning Algorithms using Evolutionary and Discrete Gradient Approaches. Artificial Intelligence and Applications 2005: 761-766

Ranadhir Ghosh, Moumita Ghosh, John Yearwood, Adil M. Bagirov: Comparative Analysis of Genetic Algorithm, Simulated Annealing and Cutting Angle Method for Artificial Neural Networks. MLDM 2005: 62-70

Ranadhir Ghosh, Moumita Ghosh, John Yearwood, Adil M. Bagirov: Determining Regularization Parameters for Derivative Free Neural Learning. MLDM 2005: 71-79

Leonid Churilov, Adil M. Bagirov, Daniel Schwartz, Kate A. Smith, Michael Dally: Improving Risk Grouping Rules for Prostate Cancer Patients with Optimization. HICSS 2004

Adil M. Bagirov, Brent Ferguson, Sasha Ivkovic, G. Saunders, John Yearwood: New algorithms for multi-class cancer diagnosis using tumor gene expression signatures. Bioinformatics 19(14): 1800-1807 (2003)

Hussein A. Abbass, Adil M. Bagirov, J. Zhang: The discrete gradient evolutionary strategy method for global optimization. IEEE Congress on Evolutionary Computation (1) 2003: 435-442

Adil M. Bagirov, Leonid Churilov: An Optimization-Based Approach to Patient Grouping for Acute Healthcare in Australia. International Conference on Computational Science 2003: 20-29

Gleb Beliakov, J. E. Monsalve Tobon, Adil M. Bagirov: Parallelization of the Discrete Gradient Method of Non-smooth Optimization and Its Applications. International Conference on Computational Science 2003: 592-601

Adil M. Bagirov, Alex Rubinov, John Yearwood, Andrew Stranieri: A Global Optimization Approach to Classification in Medical Diagnosis and Prognosis. HICSS 2001