Adil M. Bagirov

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 35

Top Topics

Linear Regression

Unsupervised Classification

Top Venues

J. Glob. Optim.

Pattern Recognit.

Optim. Methods Softw.

Publications

Sona Taheri, Adil M. Bagirov, Nargiz Sultanova, Burak Ordin
Robust clustering algorithm: The use of soft trimming approach. Pattern Recognit. Lett. 185 (2024)
Adil M. Bagirov, Ramiz M. Aliguliyev, Nargiz Sultanova
Finding compact and well-separated clusters: Clustering using silhouette coefficients. Pattern Recognit. 135 (2023)
Adil M. Bagirov, Najmeh Hoseini Monjezi, Sona Taheri
A novel optimization approach towards improving separability of clusters. Comput. Oper. Res. 152 (2023)
Qiang Long, Adil M. Bagirov, Sona Taheri, Nargiz Sultanova, Xue Wu
Methods and Applications of Clusterwise Linear Regression: A Survey and Comparison. ACM Trans. Knowl. Discov. Data 17 (3) (2023)
Manlio Gaudioso, Sona Taheri, Adil M. Bagirov, Napsu Karmitsa
Bundle Enrichment Method for Nonsmooth Difference of Convex Programming Problems. Algorithms 16 (8) (2023)
Adil M. Bagirov, Sona Taheri, Fusheng Bai, Fangying Zheng
Nonsmooth Optimization-Based Model and Algorithm for Semisupervised Clustering. IEEE Trans. Neural Networks Learn. Syst. 34 (9) (2023)
Napsu Karmitsa, Sona Taheri, Kaisa Joki, Pauliina Paasivirta, Adil M. Bagirov, Marko M. Mäkelä
Nonsmooth Optimization-Based Hyperparameter-Free Neural Networks for Large-Scale Regression. Algorithms 16 (9) (2023)
Adil M. Bagirov, Sona Taheri, Napsu Karmitsa, Nargiz Sultanova, Soodabeh Asadi
-regression via nonsmooth DC optimization. Optim. Methods Softw. 37 (4) (2022)
Napsu Karmitsa, Sona Taheri, Adil M. Bagirov, Pauliina Mäkinen
Missing Value Imputation via Clusterwise Linear Regression. IEEE Trans. Knowl. Data Eng. 34 (4) (2022)
Adil M. Bagirov, Sona Taheri, Emre Çimen
Incremental DC optimization algorithm for large-scale clusterwise linear regression. J. Comput. Appl. Math. 389 (2021)
Adil M. Bagirov, Sona Taheri, Kaisa Joki, Napsu Karmitsa, Marko M. Mäkelä
Aggregate subgradient method for nonsmooth DC optimization. Optim. Lett. 15 (1) (2021)
Adil M. Bagirov, Najmeh Hoseini Monjezi, Sona Taheri
An augmented subgradient method for minimizing nonsmooth DC functions. Comput. Optim. Appl. 80 (2) (2021)
Md. Moniruzzaman, Adil M. Bagirov, Iqbal Gondal
Partial Undersampling of Imbalanced Data for Cyber Threats Detection. ACSW (2020)
Sona Taheri, Adil M. Bagirov, Iqbal Gondal, Simon Brown
Cyberattack triage using incremental clustering for intrusion detection systems. Int. J. Inf. Sec. 19 (5) (2020)
Alejandro Estrada-Moreno, Alberto Ferrer, Angel A. Juan, Adil M. Bagirov, Javier Panadero
A biased-randomised algorithm for the capacitated facility location problem with soft constraints. J. Oper. Res. Soc. 71 (11) (2020)
Igor Grigoryev, Adil M. Bagirov, Michael Tuck
Prediction of gold-bearing localised occurrences from limited exploration data. Int. J. Comput. Sci. Eng. 21 (4) (2020)
Kaisa Joki, Adil M. Bagirov, Napsu Karmitsa, Marko M. Mäkelä, Sona Taheri
Clusterwise support vector linear regression. Eur. J. Oper. Res. 287 (1) (2020)
Adil M. Bagirov, Karim Mardaneh
New gene selection algorithm using hypeboxes to improve performance of classifiers. Int. J. Bioinform. Res. Appl. 16 (3) (2020)
Adil M. Bagirov, Gürkan Öztürk, Refail Kasimbeyli
A sharp augmented Lagrangian-based method in constrained non-convex optimization. Optim. Methods Softw. 34 (3) (2019)
Syed Quddus, Adil M. Bagirov
A Comparative Study of Unsupervised Classification Algorithms in Multi-Sized Data Sets. AICCC (2019)
Sona Taheri, Iqbal Gondal, Adil M. Bagirov, Greg Harkness, Simon Brown, CHihung Chi
Multi-Source Cyber-Attacks Detection using Machine Learning. ICIT (2019)
Sattar Seifollahi, Adil M. Bagirov, Ehsan Zare Borzeshi, Massimo Piccardi
A simulated annealing-based maximum-margin clustering algorithm. Comput. Intell. 35 (1) (2019)
Kaisa Joki, Adil M. Bagirov, Napsu Karmitsa, Marko M. Mäkelä, Sona Taheri
Double Bundle Method for finding Clarke Stationary Points in Nonsmooth DC Programming. SIAM J. Optim. 28 (2) (2018)
Adil M. Bagirov, Sattar Seifollahi, Massimo Piccardi, Ehsan Zare Borzeshi, Bernie Kruger
SMGKM: An Efficient Incremental Algorithm for Clustering Document Collections. CICLing (2) (2018)
Manlio Gaudioso, Giovanni Giallombardo, Giovanna Miglionico, Adil M. Bagirov
Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations. J. Glob. Optim. 71 (1) (2018)
Md. Moniruzzaman, Adil M. Bagirov, Iqbal Gondal, Simon Brown
A Server Side Solution for Detecting WebInject: A Machine Learning Approach. PAKDD (Workshops) (2018)
Napsu Karmitsa, Adil M. Bagirov, Sona Taheri
Clustering in large data sets with the limited memory bundle method. Pattern Recognit. 83 (2018)
Kok Lay Teo, Adil M. Bagirov, Wuyi Yue
Preface of the special issue: the 6th International Conference on Optimization and Control with Applications (6th OCA). Optim. Lett. 12 (6) (2018)
Adil M. Bagirov, Julien Ugon
Nonsmooth DC programming approach to clusterwise linear regression: optimality conditions and algorithms. Optim. Methods Softw. 33 (1) (2018)
Kaisa Joki, Adil M. Bagirov, Napsu Karmitsa, Marko M. Mäkelä
A proximal bundle method for nonsmooth DC optimization utilizing nonconvex cutting planes. J. Glob. Optim. 68 (3) (2017)
Napsu Karmitsa, Adil M. Bagirov, Sona Taheri
New diagonal bundle method for clustering problems in large data sets. Eur. J. Oper. Res. 263 (2) (2017)
Sattar Seifollahi, Adil M. Bagirov, Robert Layton, Iqbal Gondal
Optimization Based Clustering Algorithms for Authorship Analysis of Phishing Emails. Neural Process. Lett. 46 (2) (2017)
Ehsan Mohebi, Adil M. Bagirov
Constrained Self Organizing Maps for Data Clusters Visualization. Neural Process. Lett. 43 (3) (2016)
Adil M. Bagirov, Ehsan Mohebi
-Norm Based on Hyperbolic Smoothing Technique. Comput. Intell. 32 (3) (2016)
Adil M. Bagirov, Sona Taheri, Julien Ugon
Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems. Pattern Recognit. 53 (2016)
Adil M. Bagirov, Burak Ordin, Gürkan Öztürk, Adilson Elias Xavier
An incremental clustering algorithm based on hyperbolic smoothing. Comput. Optim. Appl. 61 (1) (2015)
Burak Ordin, Adil M. Bagirov
A heuristic algorithm for solving the minimum sum-of-squares clustering problems. J. Glob. Optim. 61 (2) (2015)
Ehsan Mohebi, Adil M. Bagirov
Modified self-organising maps with a new topology and initialisation algorithm. J. Exp. Theor. Artif. Intell. 27 (3) (2015)
Alberto Ferrer, Adil M. Bagirov, Gleb Beliakov
Solving DC programs using the cutting angle method. J. Glob. Optim. 61 (1) (2015)
Gürkan Öztürk, Adil M. Bagirov, Refail Kasimbeyli
An incremental piecewise linear classifier based on polyhedral conic separation. Mach. Learn. 101 (1-3) (2015)
Adil M. Bagirov, Julien Ugon, Hijran G. Mirzayeva
Nonsmooth Optimization Algorithm for Solving Clusterwise Linear Regression Problems. J. Optim. Theory Appl. 164 (3) (2015)
Adil M. Bagirov, Julien Ugon, Hijran G. Mirzayeva
An algorithm for clusterwise linear regression based on smoothing techniques. Optim. Lett. 9 (2) (2015)
Herbert F. Jelinek, Andrew Yatsko, Andrew Stranieri, Sitalakshmi Venkatraman, Adil M. Bagirov
Diagnostic with incomplete nominal/discrete data. Artif. Intell. Res. 4 (1) (2015)
Ali Hakan Tor, Adil M. Bagirov, Bülent Karasözen
Aggregate codifferential method for nonsmooth DC optimization. J. Comput. Appl. Math. 259 (2014)
Adil M. Bagirov, Kaisa Miettinen, Gerhard-Wilhelm Weber
Preface of the special issue OR: connecting sciences supported by global optimization related to the 25th European conference on operational research (EURO XXV 2012). J. Glob. Optim. 60 (1) (2014)
Ehsan Mohebi, Adil M. Bagirov
CR-Modified SOM to the Problem of Handwritten Digits Recognition. SGAI Conf. (2014)
Ehsan Mohebi, Adil M. Bagirov
A convolutional recursive modified Self Organizing Map for handwritten digits recognition. Neural Networks 60 (2014)
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. Math. Comput. Model. 57 (3-4) (2013)
Adil M. Bagirov, Julien Ugon, Hijran G. Mirzayeva
Nonsmooth nonconvex optimization approach to clusterwise linear regression problems. Eur. J. Oper. Res. 229 (1) (2013)
Adil M. Bagirov, L. Jin, Napsu Karmitsa, A. Al Nuaimat, Napsu Sultanova
Subgradient Method for Nonconvex Nonsmooth Optimization. J. Optim. Theory Appl. 157 (2) (2013)
N. M. S. Karmitsa, Adil M. Bagirov, Marko M. Mäkelä
Comparing different nonsmooth minimization methods and software. Optim. Methods Softw. 27 (1) (2012)
Sona Taheri, Musa Mammadov, Adil M. Bagirov
Improving Naive Bayes Classifier Using Conditional Probabilities. AusDM (2011)
Adil M. Bagirov, Julien Ugon, Dean Webb
An efficient algorithm for the incremental construction of a piecewise linear classifier. Inf. Syst. 36 (4) (2011)
Adil M. Bagirov, Julien Ugon, Dean Webb, Bülent Karasözen
Classification through incremental max-min separability. Pattern Anal. Appl. 14 (2) (2011)
Adil M. Bagirov, Andrew Yatsko, Andrew Stranieri, Herbert F. Jelinek
Feature Selection using Misclassification Counts. AusDM (2011)
Adil M. Bagirov, Julien Ugon, Dean Webb
Fast modified global k-means algorithm for incremental cluster construction. Pattern Recognit. 44 (4) (2011)
John Yearwood, Adil M. Bagirov, Sattar Seifollahi
A novel hybrid neural learning algorithm using simulated annealing and quasisecant method. AusDM (2011)
Adil M. Bagirov, Julien Ugon
Codifferential method for minimizing nonsmooth DC functions. J. Glob. Optim. 50 (1) (2011)
Adil M. Bagirov, Conny Clausen, Michael Kohler
An algorithm for the estimation of a regression function by continuous piecewise linear functions. Comput. Optim. Appl. 45 (1) (2010)
Adil M. Bagirov, Conny Clausen, Michael Kohler
An L2-boosting algorithm for estimation of a regression function. IEEE Trans. Inf. Theory 56 (3) (2010)
Adil M. Bagirov, Asef Nazari Ganjehlou
A quasisecant method for minimizing nonsmooth functions. Optim. Methods Softw. 25 (1) (2010)
Adil M. Bagirov, Conny Clausen, Michael Kohler
Estimation of a Regression Function by Maxima of Minima of Linear Functions. IEEE Trans. Inf. Theory 55 (2) (2009)
Adil M. Bagirov, Asef Nazari Ganjehlou
An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization. Math. Methods Oper. Res. 67 (2) (2008)
Adil M. Bagirov
Modified global k-means algorithm for minimum sum-of-squares clustering problems. Pattern Recognit. 41 (10) (2008)
Sol Hart, John Yearwood, Adil M. Bagirov
Visual Tools for Analysing Evolution, Emergence, and Error in Data Streams. ACIS-ICIS (2007)
Adil M. Bagirov, John Yearwood
A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems. Eur. J. Oper. Res. 170 (2) (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) (2006)
Ranadhir Ghosh, Moumita Ghosh, Adil M. Bagirov
Derivative Free Stochastic Discrete Gradient Method with Adaptive Mutation. ICDM (2006)
Adil M. Bagirov, Julien Ugon
Piecewise Partially Separable Functions and a Derivative-free Algorithm for Large Scale Nonsmooth Optimization. J. Glob. Optim. 35 (2) (2006)
Adil M. Bagirov
Max-min separability. Optim. Methods Softw. 20 (2-3) (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)
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)
Adil M. Bagirov, Alexander M. Rubinov, Jiapu Zhang
Local Optimization Method with Global Multidimensional Search. J. Glob. Optim. 32 (2) (2005)
Ranadhir Ghosh, Moumita Ghosh, John Yearwood, Adil M. Bagirov
Determining Regularization Parameters for Derivative Free Neural Learning. MLDM (2005)
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. Manag. Inf. Syst. 21 (4) (2005)
Leonid Churilov, Adil M. Bagirov, Daniel Schwartz, Kate A. Smith, Michael Dally
Improving Risk Grouping Rules for Prostate Cancer Patients with Optimization. HICSS (2004)
Hussein A. Abbass, Adil M. Bagirov, Jiapu Zhang
The discrete gradient evolutionary strategy method for global optimization. IEEE Congress on Evolutionary Computation (2003)
Adil M. Bagirov, Brent Ferguson, Sasha Ivkovic, G. Saunders, John Yearwood
New algorithms for multi-class cancer diagnosis using tumor gene expression signatures. Bioinform. 19 (14) (2003)
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)
Adil M. Bagirov, Leonid Churilov
An Optimization-Based Approach to Patient Grouping for Acute Healthcare in Australia. International Conference on Computational Science (2003)
Adil M. Bagirov, Alexander M. Rubinov
Cutting Angle Method and a Local Search. J. Glob. Optim. 27 (2-3) (2003)
Vladimir F. Demyanov, Adil M. Bagirov, Alexander M. Rubinov
A method of truncated codifferential with application to some problems of cluster analysis. J. Glob. Optim. 23 (1) (2002)
Alex M. Rubinov, X. Q. Yang, Adil M. Bagirov
Penalty functions with a small penalty parameter. Optim. Methods Softw. 17 (5) (2002)
Adil M. Bagirov
A Method for Minimization of Quasidifferentiable Functions. Optim. Methods Softw. 17 (1) (2002)
Adil M. Bagirov, Alexander M. Rubinov
Global Optimization of Marginal Functions with Applications to Economic Equilibrium. J. Glob. Optim. 20 (3-4) (2001)
Adil M. Bagirov, Alexander M. Rubinov, John Yearwood, Andrew Stranieri
A Global Optimization Approach to Classification in Medical Diagnosis and Prognosis. HICSS (2001)
Adil M. Bagirov, Alexander M. Rubinov
Global Minimization of Increasing Positively Homogeneous Functions over the Unit Simplex. Ann. Oper. Res. 98 (1-4) (2000)