Adil M. Bagirov

According to our database, Adil M. Bagirov authored at least 92 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Fuzzy Multiview Graph Learning on Sparse Electronic Health Records.

Tao Tang, Zhuoyang Han, Shuo Yu, Adil M. Bagirov, Qiang Zhang

IEEE Trans. Fuzzy Syst., October, 2024

Robust clustering algorithm: The use of soft trimming approach.

Sona Taheri, Adil M. Bagirov, Nargiz Sultanova, Burak Ordin

Pattern Recognit. Lett., 2024

2023

Nonsmooth Optimization-Based Model and Algorithm for Semisupervised Clustering.

Adil M. Bagirov, Sona Taheri, Fusheng Bai, Fangying Zheng

IEEE Trans. Neural Networks Learn. Syst., September, 2023

Methods and Applications of Clusterwise Linear Regression: A Survey and Comparison.

Qiang Long, Adil M. Bagirov, Sona Taheri, Nargiz Sultanova, Xue Wu

ACM Trans. Knowl. Discov. Data, April, 2023

A novel optimization approach towards improving separability of clusters.

Adil M. Bagirov, Najmeh Hoseini Monjezi, Sona Taheri

Comput. Oper. Res., April, 2023

Finding compact and well-separated clusters: Clustering using silhouette coefficients.

Adil M. Bagirov, Ramiz M. Aliguliyev, Nargiz Sultanova

Pattern Recognit., 2023

Nonsmooth Optimization-Based Hyperparameter-Free Neural Networks for Large-Scale Regression.

Napsu Karmitsa, Sona Taheri, Kaisa Joki, Pauliina Paasivirta, Adil M. Bagirov, Marko M. Mäkelä

Algorithms, 2023

Bundle Enrichment Method for Nonsmooth Difference of Convex Programming Problems.

Manlio Gaudioso, Sona Taheri, Adil M. Bagirov, Napsu Karmitsa

Algorithms, 2023

2022

Missing Value Imputation via Clusterwise Linear Regression.

Napsu Karmitsa, Sona Taheri, Adil M. Bagirov, Pauliina Mäkinen

IEEE Trans. Knowl. Data Eng., 2022

Robust piecewise linear <i>L</i>₁-regression via nonsmooth DC optimization.

Adil M. Bagirov, Sona Taheri, Napsu Karmitsa, Nargiz Sultanova, Soodabeh Asadi

Optim. Methods Softw., 2022

2021

Aggregate subgradient method for nonsmooth DC optimization.

Adil M. Bagirov, Sona Taheri, Kaisa Joki, Napsu Karmitsa, Marko M. Mäkelä

Optim. Lett., 2021

Incremental DC optimization algorithm for large-scale clusterwise linear regression.

Adil M. Bagirov, Sona Taheri, Emre Çimen

J. Comput. Appl. Math., 2021

An augmented subgradient method for minimizing nonsmooth DC functions.

Adil M. Bagirov, Najmeh Hoseini Monjezi, Sona Taheri

Comput. Optim. Appl., 2021

2020

A biased-randomised algorithm for the capacitated facility location problem with soft constraints.

Alejandro Estrada-Moreno, Alberto Ferrer, Angel A. Juan, Adil M. Bagirov, Javier Panadero

J. Oper. Res. Soc., 2020

Cyberattack triage using incremental clustering for intrusion detection systems.

Sona Taheri, Adil M. Bagirov, Iqbal Gondal, Simon Brown

Int. J. Inf. Sec., 2020

Prediction of gold-bearing localised occurrences from limited exploration data.

Igor Grigoryev, Adil M. Bagirov, Michael Tuck

Int. J. Comput. Sci. Eng., 2020

New gene selection algorithm using hypeboxes to improve performance of classifiers.

Adil M. Bagirov, Karim Mardaneh

Int. J. Bioinform. Res. Appl., 2020

Clusterwise support vector linear regression.

Kaisa Joki, Adil M. Bagirov, Napsu Karmitsa, Marko M. Mäkelä, Sona Taheri

Eur. J. Oper. Res., 2020

Partial Undersampling of Imbalanced Data for Cyber Threats Detection.

Md. Moniruzzaman, Adil M. Bagirov, Iqbal Gondal

Proceedings of the Australasian Computer Science Week, 2020

2019

A sharp augmented Lagrangian-based method in constrained non-convex optimization.

Adil M. Bagirov, Gürkan Öztürk, Refail Kasimbeyli

Optim. Methods Softw., 2019

A simulated annealing-based maximum-margin clustering algorithm.

Sattar Seifollahi, Adil M. Bagirov, Ehsan Zare Borzeshi, Massimo Piccardi

Comput. Intell., 2019

Multi-Source Cyber-Attacks Detection using Machine Learning.

Sona Taheri, Iqbal Gondal, Adil M. Bagirov, Greg Harkness, Simon Brown, CHihung Chi

Proceedings of the IEEE International Conference on Industrial Technology, 2019

A Comparative Study of Unsupervised Classification Algorithms in Multi-Sized Data Sets.

Syed Quddus, Adil M. Bagirov

Proceedings of the AICCC 2019: 2nd Artificial Intelligence and Cloud Computing Conference, 2019

2018

Double Bundle Method for finding Clarke Stationary Points in Nonsmooth DC Programming.

Kaisa Joki, Adil M. Bagirov, Napsu Karmitsa, Marko M. Mäkelä, Sona Taheri

SIAM J. Optim., 2018

Clustering in large data sets with the limited memory bundle method.

Napsu Karmitsa, Adil M. Bagirov, Sona Taheri

Pattern Recognit., 2018

Nonsmooth DC programming approach to clusterwise linear regression: optimality conditions and algorithms.

Adil M. Bagirov, Julien Ugon

Optim. Methods Softw., 2018

Preface of the special issue: the 6th International Conference on Optimization and Control with Applications (6th OCA).

Kok Lay Teo, Adil M. Bagirov, Wuyi Yue

Optim. Lett., 2018

Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations.

Manlio Gaudioso, Giovanni Giallombardo, Giovanna Miglionico, Adil M. Bagirov

J. Glob. Optim., 2018

A Server Side Solution for Detecting WebInject: A Machine Learning Approach.

Md. Moniruzzaman, Adil M. Bagirov, Iqbal Gondal, Simon Brown

Proceedings of the Trends and Applications in Knowledge Discovery and Data Mining, 2018

SMGKM: An Efficient Incremental Algorithm for Clustering Document Collections.

Adil M. Bagirov, Sattar Seifollahi, Massimo Piccardi, Ehsan Zare Borzeshi, Bernie Kruger

Proceedings of the Computational Linguistics and Intelligent Text Processing, 2018

2017

Optimization Based Clustering Algorithms for Authorship Analysis of Phishing Emails.

Sattar Seifollahi, Adil M. Bagirov, Robert Layton, Iqbal Gondal

Neural Process. Lett., 2017

A proximal bundle method for nonsmooth DC optimization utilizing nonconvex cutting planes.

Kaisa Joki, Adil M. Bagirov, Napsu Karmitsa, Marko M. Mäkelä

J. Glob. Optim., 2017

New diagonal bundle method for clustering problems in large data sets.

Napsu Karmitsa, Adil M. Bagirov, Sona Taheri

Eur. J. Oper. Res., 2017

2016

Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems.

Adil M. Bagirov, Sona Taheri, Julien Ugon

Pattern Recognit., 2016

Constrained Self Organizing Maps for Data Clusters Visualization.

Ehsan Mohebi, Adil M. Bagirov

Neural Process. Lett., 2016

An Algorithm for Clustering Using <i>L</i>₁-Norm Based on Hyperbolic Smoothing Technique.

Adil M. Bagirov, Ehsan Mohebi

Comput. Intell., 2016

2015

An algorithm for clusterwise linear regression based on smoothing techniques.

Adil M. Bagirov, Julien Ugon, Hijran G. Mirzayeva

Optim. Lett., 2015

An incremental piecewise linear classifier based on polyhedral conic separation.

Gürkan Öztürk, Adil M. Bagirov, Refail Kasimbeyli

Mach. Learn., 2015

Nonsmooth Optimization Algorithm for Solving Clusterwise Linear Regression Problems.

Adil M. Bagirov, Julien Ugon, Hijran G. Mirzayeva

J. Optim. Theory Appl., 2015

A heuristic algorithm for solving the minimum sum-of-squares clustering problems.

Burak Ordin, Adil M. Bagirov

J. Glob. Optim., 2015

Solving DC programs using the cutting angle method.

Alberto Ferrer, Adil M. Bagirov, Gleb Beliakov

J. Glob. Optim., 2015

Modified self-organising maps with a new topology and initialisation algorithm.

Ehsan Mohebi, Adil M. Bagirov

J. Exp. Theor. Artif. Intell., 2015

An incremental clustering algorithm based on hyperbolic smoothing.

Adil M. Bagirov, Burak Ordin, Gürkan Öztürk, Adilson Elias Xavier

Comput. Optim. Appl., 2015

Diagnostic with incomplete nominal/discrete data.

Herbert F. Jelinek, Andrew Yatsko, Andrew Stranieri, Sitalakshmi Venkatraman, Adil M. Bagirov

Artif. Intell. Res., 2015

2014

A convolutional recursive modified Self Organizing Map for handwritten digits recognition.

Ehsan Mohebi, Adil M. Bagirov

Neural Networks, 2014

Preface of the special issue OR: connecting sciences supported by global optimization related to the 25th European conference on operational research (EURO XXV 2012).

Adil M. Bagirov, Kaisa Miettinen, Gerhard-Wilhelm Weber

J. Glob. Optim., 2014

Aggregate codifferential method for nonsmooth DC optimization.

Ali Hakan Tor, Adil M. Bagirov, Bülent Karasözen

J. Comput. Appl. Math., 2014

CR-Modified SOM to the Problem of Handwritten Digits Recognition.

Ehsan Mohebi, Adil M. Bagirov

Proceedings of the Research and Development in Intelligent Systems XXXI, 2014

2013

An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling.

Adil M. Bagirov, A. F. Barton, H. Mala-Jetmarova, A. Al Nuaimat, S. T. Ahmed, Napsu Sultanova, John Yearwood

Math. Comput. Model., 2013

Subgradient Method for Nonconvex Nonsmooth Optimization.

Adil M. Bagirov, L. Jin, Napsu Karmitsa, A. Al Nuaimat, Napsu Sultanova

J. Optim. Theory Appl., 2013

Nonsmooth nonconvex optimization approach to clusterwise linear regression problems.

Adil M. Bagirov, Julien Ugon, Hijran G. Mirzayeva

Eur. J. Oper. Res., 2013

2012

Comparing different nonsmooth minimization methods and software.

N. M. S. Karmitsa, Adil M. Bagirov, Marko M. Mäkelä

Optim. Methods Softw., 2012

2011

Fast modified global k-means algorithm for incremental cluster construction.

Adil M. Bagirov, Julien Ugon, Dean Webb

Pattern Recognit., 2011

Classification through incremental max-min separability.

Adil M. Bagirov, Julien Ugon, Dean Webb, Bülent Karasözen

Pattern Anal. Appl., 2011

Codifferential method for minimizing nonsmooth DC functions.

Adil M. Bagirov, Julien Ugon

J. Glob. Optim., 2011

An efficient algorithm for the incremental construction of a piecewise linear classifier.

Adil M. Bagirov, Julien Ugon, Dean Webb

Inf. Syst., 2011

A novel hybrid neural learning algorithm using simulated annealing and quasisecant method.

John Yearwood, Adil M. Bagirov, Sattar Seifollahi

Proceedings of the Ninth Australasian Data Mining Conference, AusDM 2011, Ballarat, 2011

Improving Naive Bayes Classifier Using Conditional Probabilities.

Sona Taheri, Musa Mammadov, Adil M. Bagirov

Proceedings of the Ninth Australasian Data Mining Conference, AusDM 2011, Ballarat, 2011

Feature Selection using Misclassification Counts.

Adil M. Bagirov, Andrew Yatsko, Andrew Stranieri, Herbert F. Jelinek

Proceedings of the Ninth Australasian Data Mining Conference, AusDM 2011, Ballarat, 2011

2010

An L2-boosting algorithm for estimation of a regression function.

Adil M. Bagirov, Conny Clausen, Michael Kohler

IEEE Trans. Inf. Theory, 2010

A quasisecant method for minimizing nonsmooth functions.

Adil M. Bagirov, Asef Nazari Ganjehlou

Optim. Methods Softw., 2010

An algorithm for the estimation of a regression function by continuous piecewise linear functions.

Adil M. Bagirov, Conny Clausen, Michael Kohler

Comput. Optim. Appl., 2010

2009

Global Optimization: Cutting Angle Method.

Adil M. Bagirov, Gleb Beliakov

Proceedings of the Encyclopedia of Optimization, Second Edition, 2009

Nonsmooth Optimization Approach to Clustering.

Adil M. Bagirov

Proceedings of the Encyclopedia of Optimization, Second Edition, 2009

Derivative-Free Methods for Non-smooth Optimization.

Adil M. Bagirov

Proceedings of the Encyclopedia of Optimization, Second Edition, 2009

Continuous Approximations to Subdifferentials.

Adil M. Bagirov

Proceedings of the Encyclopedia of Optimization, Second Edition, 2009

Estimation of a Regression Function by Maxima of Minima of Linear Functions.

Adil M. Bagirov, Conny Clausen, Michael Kohler

IEEE Trans. Inf. Theory, 2009

2008

Modified global k-means algorithm for minimum sum-of-squares clustering problems.

Adil M. Bagirov

Pattern Recognit., 2008

An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization.

Adil M. Bagirov, Asef Nazari Ganjehlou

Math. Methods Oper. Res., 2008

2007

Visual Tools for Analysing Evolution, Emergence, and Error in Data Streams.

Sol Hart, John Yearwood, Adil M. Bagirov

Proceedings of the 6th Annual IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), 2007

2006

Piecewise Partially Separable Functions and a Derivative-free Algorithm for Large Scale Nonsmooth Optimization.

Adil M. Bagirov, Julien Ugon

J. Glob. Optim., 2006

A Hybrid Neural Learning Algorithm Using Evolutionary Learning and Derivative Free Local Search Method.

Ranadhir Ghosh, John Yearwood, Moumita Ghosh, Adil M. Bagirov

Int. J. Neural Syst., 2006

A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems.

Adil M. Bagirov, John Yearwood

Eur. J. Oper. Res., 2006

Derivative Free Stochastic Discrete Gradient Method with Adaptive Mutation.

Ranadhir Ghosh, Moumita Ghosh, Adil M. Bagirov

Proceedings of the Advances in Data Mining, 2006

2005

Max-min separability.

Adil M. Bagirov

Optim. Methods Softw., 2005

Data Mining with Combined Use of Optimization Techniques and Self-Organizing Maps for Improving Risk Grouping Rules: Application to Prostate Cancer Patients.

Leonid Churilov, Adil M. Bagirov, Daniel Schwartz, Kate A. Smith, Michael Dally

J. Manag. Inf. Syst., 2005

Local Optimization Method with Global Multidimensional Search.

Adil M. Bagirov, Alexander M. Rubinov, Jiapu Zhang

J. Glob. Optim., 2005

Determining Regularization Parameters for Derivative Free Neural Learning.

Ranadhir Ghosh, Moumita Ghosh, John Yearwood, Adil M. Bagirov

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Comparative Analysis of Genetic Algorithm, Simulated Annealing and Cutting Angle Method for Artificial Neural Networks.

Ranadhir Ghosh, Moumita Ghosh, John Yearwood, Adil M. Bagirov

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Fusion Strategies for Neural Learning Algorithms using Evolutionary and Discrete Gradient Approaches.

Ranadhir Ghosh, John Yearwood, Moumita Ghosh, Adil M. Bagirov

Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, 2005

2004

Improving Risk Grouping Rules for Prostate Cancer Patients with Optimization.

Leonid Churilov, Adil M. Bagirov, Daniel Schwartz, Kate A. Smith, Michael Dally

Proceedings of the 37th Hawaii International Conference on System Sciences (HICSS-37 2004), 2004

2003

Cutting Angle Method and a Local Search.

Adil M. Bagirov, Alexander M. Rubinov

J. Glob. Optim., 2003

New algorithms for multi-class cancer diagnosis using tumor gene expression signatures.

Adil M. Bagirov, Brent Ferguson, Sasha Ivkovic, G. Saunders, John Yearwood

Bioinform., 2003

Parallelization of the Discrete Gradient Method of Non-smooth Optimization and Its Applications.

Gleb Beliakov, J. E. Monsalve Tobon, Adil M. Bagirov

Proceedings of the Computational Science - ICCS 2003, 2003

An Optimization-Based Approach to Patient Grouping for Acute Healthcare in Australia.

Adil M. Bagirov, Leonid Churilov

Proceedings of the Computational Science - ICCS 2003, 2003

The discrete gradient evolutionary strategy method for global optimization.

Hussein A. Abbass, Adil M. Bagirov, Jiapu Zhang

Proceedings of the IEEE Congress on Evolutionary Computation, 2003

2002

Penalty functions with a small penalty parameter.

Alex M. Rubinov, X. Q. Yang, Adil M. Bagirov

Optim. Methods Softw., 2002

A Method for Minimization of Quasidifferentiable Functions.

Adil M. Bagirov

Optim. Methods Softw., 2002

A method of truncated codifferential with application to some problems of cluster analysis.

Vladimir F. Demyanov, Adil M. Bagirov, Alexander M. Rubinov

J. Glob. Optim., 2002

2001

Global Optimization of Marginal Functions with Applications to Economic Equilibrium.

Adil M. Bagirov, Alexander M. Rubinov

J. Glob. Optim., 2001

A Global Optimization Approach to Classification in Medical Diagnosis and Prognosis.

Adil M. Bagirov, Alexander M. Rubinov, John Yearwood, Andrew Stranieri

Proceedings of the 34th Annual Hawaii International Conference on System Sciences (HICSS-34), 2001

2000

Global Minimization of Increasing Positively Homogeneous Functions over the Unit Simplex.

Adil M. Bagirov, Alexander M. Rubinov

Ann. Oper. Res., 2000