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Adil M. Bagirov
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2020 – today
- 2024
- [j69]Sona Taheri
, Adil M. Bagirov
Robust clustering algorithm: The use of soft trimming approach. Pattern Recognit. Lett. 185: 15-22 (2024) - [j68]Tao Tang
Fuzzy Multiview Graph Learning on Sparse Electronic Health Records. IEEE Trans. Fuzzy Syst. 32(10): 5520-5532 (2024) - 2023
- [j67]Manlio Gaudioso, Sona Taheri
Bundle Enrichment Method for Nonsmooth Difference of Convex Programming Problems. Algorithms 16(8): 394 (2023) - [j66]Napsu Karmitsa
Nonsmooth Optimization-Based Hyperparameter-Free Neural Networks for Large-Scale Regression. Algorithms 16(9): 444 (2023) - [j65]Adil M. Bagirov, Najmeh Hoseini Monjezi
A novel optimization approach towards improving separability of clusters. Comput. Oper. Res. 152: 106135 (2023) - [j64]Adil M. Bagirov, Ramiz M. Aliguliyev
Finding compact and well-separated clusters: Clustering using silhouette coefficients. Pattern Recognit. 135: 109144 (2023) - [j63]Qiang Long
Methods and Applications of Clusterwise Linear Regression: A Survey and Comparison. ACM Trans. Knowl. Discov. Data 17(3): 36:1-36:54 (2023) - [j62]Adil M. Bagirov
Nonsmooth Optimization-Based Model and Algorithm for Semisupervised Clustering. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5517-5530 (2023) - 2022
- [j61]Adil M. Bagirov, Sona Taheri
Robust piecewise linear L1-regression via nonsmooth DC optimization. Optim. Methods Softw. 37(4): 1289-1309 (2022) - [j60]Napsu Karmitsa
Missing Value Imputation via Clusterwise Linear Regression. IEEE Trans. Knowl. Data Eng. 34(4): 1889-1901 (2022) - 2021
- [j59]Adil M. Bagirov, Najmeh Hoseini Monjezi, Sona Taheri
An augmented subgradient method for minimizing nonsmooth DC functions. Comput. Optim. Appl. 80(2): 411-438 (2021) - [j58]Adil M. Bagirov, Sona Taheri
Incremental DC optimization algorithm for large-scale clusterwise linear regression. J. Comput. Appl. Math. 389: 113323 (2021) - [j57]Adil M. Bagirov, Sona Taheri
Aggregate subgradient method for nonsmooth DC optimization. Optim. Lett. 15(1): 83-96 (2021) - 2020
- [j56]Kaisa Joki
Clusterwise support vector linear regression. Eur. J. Oper. Res. 287(1): 19-35 (2020) - [j55]Adil M. Bagirov, Karim Mardaneh:
New gene selection algorithm using hypeboxes to improve performance of classifiers. Int. J. Bioinform. Res. Appl. 16(3): 269-289 (2020) - [j54]Igor Grigoryev, Adil M. Bagirov, Michael Tuck:
Prediction of gold-bearing localised occurrences from limited exploration data. Int. J. Comput. Sci. Eng. 21(4): 503-512 (2020) - [j53]Sona Taheri
Cyberattack triage using incremental clustering for intrusion detection systems. Int. J. Inf. Sec. 19(5): 597-607 (2020) - [j52]Alejandro Estrada-Moreno
A biased-randomised algorithm for the capacitated facility location problem with soft constraints. J. Oper. Res. Soc. 71(11): 1799-1815 (2020) - [c19]Md. Moniruzzaman, Adil M. Bagirov, Iqbal Gondal
Partial Undersampling of Imbalanced Data for Cyber Threats Detection. ACSW 2020: 9:1-9:4
2010 – 2019
- 2019
- [j51]Sattar Seifollahi
A simulated annealing-based maximum-margin clustering algorithm. Comput. Intell. 35(1): 23-41 (2019) - [j50]Adil M. Bagirov
A sharp augmented Lagrangian-based method in constrained non-convex optimization. Optim. Methods Softw. 34(3): 462-488 (2019) - [c18]Syed Quddus, Adil M. Bagirov:
A Comparative Study of Unsupervised Classification Algorithms in Multi-Sized Data Sets. AICCC 2019: 26-32 - [c17]Sona Taheri
Multi-Source Cyber-Attacks Detection using Machine Learning. ICIT 2019: 1167-1172 - 2018
- [j49]Manlio Gaudioso, Giovanni Giallombardo
Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations. J. Glob. Optim. 71(1): 37-55 (2018) - [j48]Kok Lay Teo, Adil M. Bagirov
Preface of the special issue: the 6th International Conference on Optimization and Control with Applications (6th OCA). Optim. Lett. 12(6): 1157-1159 (2018) - [j47]Adil M. Bagirov
Nonsmooth DC programming approach to clusterwise linear regression: optimality conditions and algorithms. Optim. Methods Softw. 33(1): 194-219 (2018) - [j46]Napsu Karmitsa
Clustering in large data sets with the limited memory bundle method. Pattern Recognit. 83: 245-259 (2018) - [j45]Kaisa Joki
Double Bundle Method for finding Clarke Stationary Points in Nonsmooth DC Programming. SIAM J. Optim. 28(2): 1892-1919 (2018) - [c16]Adil M. Bagirov, Sattar Seifollahi, Massimo Piccardi
SMGKM: An Efficient Incremental Algorithm for Clustering Document Collections. CICLing (2) 2018: 314-328 - [c15]Md. Moniruzzaman, Adil M. Bagirov
A Server Side Solution for Detecting WebInject: A Machine Learning Approach. PAKDD (Workshops) 2018: 162-167 - 2017
- [j44]Napsu Karmitsa
New diagonal bundle method for clustering problems in large data sets. Eur. J. Oper. Res. 263(2): 367-379 (2017) - [j43]Kaisa Joki
A proximal bundle method for nonsmooth DC optimization utilizing nonconvex cutting planes. J. Glob. Optim. 68(3): 501-535 (2017) - [j42]Sattar Seifollahi
Optimization Based Clustering Algorithms for Authorship Analysis of Phishing Emails. Neural Process. Lett. 46(2): 411-425 (2017) - 2016
- [j41]Adil M. Bagirov
An Algorithm for Clustering Using L1-Norm Based on Hyperbolic Smoothing Technique. Comput. Intell. 32(3): 439-457 (2016) - [j40]Ehsan Mohebi, Adil M. Bagirov
Constrained Self Organizing Maps for Data Clusters Visualization. Neural Process. Lett. 43(3): 849-869 (2016) - [j39]Adil M. Bagirov
Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems. Pattern Recognit. 53: 12-24 (2016) - 2015
- [j38]Herbert F. Jelinek, Andrew Yatsko, Andrew Stranieri, Sitalakshmi Venkatraman, Adil M. Bagirov:
Diagnostic with incomplete nominal/discrete data. Artif. Intell. Res. 4(1): 22-35 (2015) - [j37]Adil M. Bagirov
An incremental clustering algorithm based on hyperbolic smoothing. Comput. Optim. Appl. 61(1): 219-241 (2015) - [j36]Ehsan Mohebi, Adil M. Bagirov
Modified self-organising maps with a new topology and initialisation algorithm. J. Exp. Theor. Artif. Intell. 27(3): 351-372 (2015) - [j35]Alberto Ferrer
Solving DC programs using the cutting angle method. J. Glob. Optim. 61(1): 71-89 (2015) - [j34]Burak Ordin, Adil M. Bagirov
A heuristic algorithm for solving the minimum sum-of-squares clustering problems. J. Glob. Optim. 61(2): 341-361 (2015) - [j33]Adil M. Bagirov
Nonsmooth Optimization Algorithm for Solving Clusterwise Linear Regression Problems. J. Optim. Theory Appl. 164(3): 755-780 (2015) - [j32]Gürkan Öztürk
An incremental piecewise linear classifier based on polyhedral conic separation. Mach. Learn. 101(1-3): 397-413 (2015) - [j31]Adil M. Bagirov
An algorithm for clusterwise linear regression based on smoothing techniques. Optim. Lett. 9(2): 375-390 (2015) - 2014
- [j30]Ali Hakan Tor
Aggregate codifferential method for nonsmooth DC optimization. J. Comput. Appl. Math. 259: 851-867 (2014) - [j29]Adil M. Bagirov
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): 1-3 (2014) - [j28]Ehsan Mohebi, Adil M. Bagirov
A convolutional recursive modified Self Organizing Map for handwritten digits recognition. Neural Networks 60: 104-118 (2014) - [c14]Ehsan Mohebi, Adil M. Bagirov:
CR-Modified SOM to the Problem of Handwritten Digits Recognition. SGAI Conf. 2014: 225-238 - 2013
- [j27]Adil M. Bagirov
Nonsmooth nonconvex optimization approach to clusterwise linear regression problems. Eur. J. Oper. Res. 229(1): 132-142 (2013) - [j26]Adil M. Bagirov
Subgradient Method for Nonconvex Nonsmooth Optimization. J. Optim. Theory Appl. 157(2): 416-435 (2013) - [j25]Adil M. Bagirov
An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling. Math. Comput. Model. 57(3-4): 873-886 (2013) - 2012
- [j24]N. M. S. Karmitsa
Comparing different nonsmooth minimization methods and software. Optim. Methods Softw. 27(1): 131-153 (2012) - 2011
- [j23]Adil M. Bagirov
An efficient algorithm for the incremental construction of a piecewise linear classifier. Inf. Syst. 36(4): 782-790 (2011) - [j22]Adil M. Bagirov
Codifferential method for minimizing nonsmooth DC functions. J. Glob. Optim. 50(1): 3-22 (2011) - [j21]Adil M. Bagirov
Classification through incremental max-min separability. Pattern Anal. Appl. 14(2): 165-174 (2011) - [j20]Adil M. Bagirov
Fast modified global k-means algorithm for incremental cluster construction. Pattern Recognit. 44(4): 866-876 (2011) - [c13]Adil M. Bagirov, Andrew Yatsko, Andrew Stranieri, Herbert F. Jelinek:
Feature Selection using Misclassification Counts. AusDM 2011: 51-62 - [c12]Sona Taheri, Musa Mammadov, Adil M. Bagirov:
Improving Naive Bayes Classifier Using Conditional Probabilities. AusDM 2011: 63-68 - [c11]John Yearwood, Adil M. Bagirov, Sattar Seifollahi:
A novel hybrid neural learning algorithm using simulated annealing and quasisecant method. AusDM 2011: 205-210 - 2010
- [j19]Adil M. Bagirov
An algorithm for the estimation of a regression function by continuous piecewise linear functions. Comput. Optim. Appl. 45(1): 159-179 (2010) - [j18]Adil M. Bagirov
A quasisecant method for minimizing nonsmooth functions. Optim. Methods Softw. 25(1): 3-18 (2010) - [j17]Adil M. Bagirov
An L2-boosting algorithm for estimation of a regression function. IEEE Trans. Inf. Theory 56(3): 1417-1429 (2010)
2000 – 2009
- 2009
- [j16]Adil M. Bagirov
Estimation of a Regression Function by Maxima of Minima of Linear Functions. IEEE Trans. Inf. Theory 55(2): 833-845 (2009) - [r4]Adil M. Bagirov
Continuous Approximations to Subdifferentials. Encyclopedia of Optimization 2009: 475-482 - [r3]Adil M. Bagirov
Derivative-Free Methods for Non-smooth Optimization. Encyclopedia of Optimization 2009: 648-655 - [r2]Adil M. Bagirov
Global Optimization: Cutting Angle Method. Encyclopedia of Optimization 2009: 1304-1311 - [r1]Adil M. Bagirov
Nonsmooth Optimization Approach to Clustering. Encyclopedia of Optimization 2009: 2664-2671 - 2008
- [j15]Adil M. Bagirov
An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization. Math. Methods Oper. Res. 67(2): 187-206 (2008) - [j14]Adil M. Bagirov
Modified global k-means algorithm for minimum sum-of-squares clustering problems. Pattern Recognit. 41(10): 3192-3199 (2008) - 2007
- [c10]Sol Hart, John Yearwood, Adil M. Bagirov
Visual Tools for Analysing Evolution, Emergence, and Error in Data Streams. ACIS-ICIS 2007: 987-992 - 2006
- [j13]Adil M. Bagirov
A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems. Eur. J. Oper. Res. 170(2): 578-596 (2006) - [j12]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) - [j11]Adil M. Bagirov
Piecewise Partially Separable Functions and a Derivative-free Algorithm for Large Scale Nonsmooth Optimization. J. Glob. Optim. 35(2): 163-195 (2006) - [c9]Ranadhir Ghosh, Moumita Ghosh, Adil M. Bagirov
Derivative Free Stochastic Discrete Gradient Method with Adaptive Mutation. ICDM 2006: 264-278 - 2005
- [j10]Adil M. Bagirov
Local Optimization Method with Global Multidimensional Search. J. Glob. Optim. 32(2): 161-179 (2005) - [j9]Leonid Churilov, Adil M. Bagirov
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): 85-100 (2005) - [j8]Adil M. Bagirov
Max-min separability. Optim. Methods Softw. 20(2-3): 277-296 (2005) - [c8]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 - [c7]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 - [c6]Ranadhir Ghosh, Moumita Ghosh, John Yearwood, Adil M. Bagirov:
Determining Regularization Parameters for Derivative Free Neural Learning. MLDM 2005: 71-79 - 2004
- [c5]Leonid Churilov, Adil M. Bagirov, Daniel Schwartz, Kate A. Smith, Michael Dally:
Improving Risk Grouping Rules for Prostate Cancer Patients with Optimization. HICSS 2004 - 2003
- [j7]Adil M. Bagirov
New algorithms for multi-class cancer diagnosis using tumor gene expression signatures. Bioinform. 19(14): 1800-1807 (2003) - [j6]Adil M. Bagirov
Cutting Angle Method and a Local Search. J. Glob. Optim. 27(2-3): 193-213 (2003) - [c4]Hussein A. Abbass
The discrete gradient evolutionary strategy method for global optimization. IEEE Congress on Evolutionary Computation 2003: 435-442 - [c3]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 - [c2]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 - 2002
- [j5]Vladimir F. Demyanov
A method of truncated codifferential with application to some problems of cluster analysis. J. Glob. Optim. 23(1): 63-80 (2002) - [j4]Adil M. Bagirov
A Method for Minimization of Quasidifferentiable Functions. Optim. Methods Softw. 17(1): 31-60 (2002) - [j3]Alex M. Rubinov, X. Q. Yang, Adil M. Bagirov
Penalty functions with a small penalty parameter. Optim. Methods Softw. 17(5): 931-964 (2002) - 2001
- [j2]Adil M. Bagirov
Global Optimization of Marginal Functions with Applications to Economic Equilibrium. J. Glob. Optim. 20(3-4): 215-237 (2001) - [c1]Adil M. Bagirov
A Global Optimization Approach to Classification in Medical Diagnosis and Prognosis. HICSS 2001 - 2000
- [j1]Adil M. Bagirov, Alexander M. Rubinov:
Global Minimization of Increasing Positively Homogeneous Functions over the Unit Simplex. Ann. Oper. Res. 98(1-4): 171-187 (2000)
Coauthor Index
Napsu Karmitsa
aka: N. M. S. Karmitsa
aka: N. M. S. Karmitsa
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last updated on 2024-12-10 20:51 CET by the dblp team
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