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ORCIDJohn A. W. McCall
John McCall 0001
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- affiliation: Robert Gordon University, Aberdeen, UK
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2020 – today
- 2024
[j19]Truong Dang
, Tien Thanh Nguyen, John A. W. McCall, Eyad Elyan, Carlos Francisco Moreno-García:
Two-layer Ensemble of Deep Learning Models for Medical Image Segmentation. Cogn. Comput. 16(3): 1141-1160 (2024)- [j18]Truong Dang, Tien Thanh Nguyen, Alan Wee-Chung Liew, Eyad Elyan, John A. W. McCall:
Which classifiers are connected to others? An optimal connection framework for multi-layer ensemble systems. Knowl. Based Syst. 304: 112522 (2024) - [j17]Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Giovanni Iacca, John A. W. McCall, David J. Walker:
Introduction to the Special Issue on Explainable AI in Evolutionary Computation. ACM Trans. Evol. Learn. Optim. 4(1): 1:1-1:2 (2024) - [j16]Kate Han, Lee A. Christie, Alexandru-Ciprian Zavoianu, John A. W. McCall:
Exploring Representations for Optimizing Connected Autonomous Vehicle Routes in Multi-Modal Transport Networks Using Evolutionary Algorithms. IEEE Trans. Intell. Transp. Syst. 25(9): 10790-10801 (2024) - [c115]Truong Dang, Tien Thanh Nguyen, John McCall, Kate Han, Alan Wee-Chung Liew:
A Novel Surrogate Model for Variable-Length Encoding and its Application in Optimising Deep Learning Architecture. CEC 2024: 1-8 - [c114]Giancarlo Antonino Pasquale Ignazio Catalano, Alexander E. I. Brownlee, David E. Cairns, John A. W. McCall, Russell Ainslie:
Mining Potentially Explanatory Patterns via Partial Solutions. GECCO Companion 2024: 567-570 - [c113]Akinola Ogunsemi, John A. W. McCall, Alexandru-Ciprian Zavoianu, Lee A. Christie:
Cost and Performance Comparison of Holistic Solution Approaches for Complex Supply Chains on a Novel Linked Problem Benchmark. GECCO 2024 - [c112]Lee A. Christie, Atakan Sahin, Akinola Ogunsemi, Alexandru-Ciprian Zavoianu, John A. W. McCall:
On the Multi-objective Optimization of Wind Farm Cable Layouts with Regard to Cost and Robustness. PPSN (4) 2024: 367-382 - [i5]GianCarlo Catalano, Alexander E. I. Brownlee, David E. Cairns, John A. W. McCall, Russell Ainslie:
Mining Potentially Explanatory Patterns via Partial Solutions. CoRR abs/2404.04388 (2024) - [i4]Ryan Zhou, Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Martin Fyvie, Giovanni Iacca, John A. W. McCall, Niki van Stein, David Walker, Ting Hu:
Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. CoRR abs/2406.07811 (2024) - 2023
- [j15]Daniel Dobos, Tien Thanh Nguyen, Truong Dang, Allan Wilson, Helen Corbett, John A. W. McCall, Phil Stockton:
A comparative study of anomaly detection methods for gross error detection problems. Comput. Chem. Eng. 175: 108263 (2023) - [j14]Anh Vu Luong, Tien Thanh Nguyen, Kate Han, Trung Hieu Vu, John McCall, Alan Wee-Chung Liew:
DEFEG: Deep Ensemble with Weighted Feature Generation. Knowl. Based Syst. 275: 110691 (2023) - [j13]Joan Alza, Mark Bartlett, Josu Ceberio, John McCall:
On the elusivity of dynamic optimisation problems. Swarm Evol. Comput. 78: 101289 (2023) - [c111]Yijun Yan, Yinhe Li, Hanhe Lin, Md. Mostafa Kamal Sarker, Jinchang Ren, John McCall:
Underwater Object Detection for Smooth and Autonomous Operations of Naval Missions: A Pilot Dataset. BICS 2023: 113-122 - [c110]Martin Fyvie, John McCall, Lee A. Christie, Alexander E. I. Brownlee:
Explaining a Staff Rostering Genetic Algorithm using Sensitivity Analysis and Trajectory Analysis. GECCO Companion 2023: 1648-1656 - [c109]Martin Fyvie, John A. W. McCall, Lee A. Christie, Alexandru-Ciprian Zavoianu, Alexander E. I. Brownlee, Russell Ainslie:
Explaining a Staff Rostering Problem by Mining Trajectory Variance Structures. SGAI Conf. 2023: 275-290 - [c108]Joseph Collins, Alexandru-Ciprian Zavoianu, John A. W. McCall:
Comparison of Simulated Annealing and Evolution Strategies for Optimising Cyclical Rosters with Uneven Demand and Flexible Trainee Placement. SGAI Conf. 2023: 451-464 - [c107]Daniel Dobos, Truong Dang, Tien Thanh Nguyen, John McCall, Allan Wilson, Helen Corbett, Phil Stockton:
A Weighted Ensemble of Regression Methods for Gross Error Identification Problem. SSCI 2023: 413-420 - 2022
- [c106]Truong Dang, Anh Vu Luong, Alan Wee-Chung Liew, John McCall, Tien Thanh Nguyen:
Ensemble of deep learning models with surrogate-based optimization for medical image segmentation. CEC 2022: 1-8 - [c105]Alexandru-Ciprian Zavoianu, Benjamin Lacroix, John McCall:
Lightweight Interpolation-Based Surrogate Modelling for Multi-objective Continuous Optimisation. EUROCAST 2022: 53-60 - [c104]Kate Han, Lee A. Christie, Alexandru-Ciprian Zavoianu, John McCall:
On Discovering Optimal Trade-Offs When Introducing New Routes in Existing Multi-modal Public Transport Systems. EUROCAST 2022: 104-111 - [c103]Akinola Ogunsemi, John A. W. McCall, Mathias Kern, Benjamin Lacroix, David Corsar, Gilbert Owusu:
Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem. GECCO Companion 2022: 735-738 - [c102]Joan Alza, Mark Bartlett, Josu Ceberio, John A. W. McCall:
Analysing the Fitness Landscape Rotation for Combinatorial Optimisation. PPSN (1) 2022: 533-547 - [c101]Akinola Ogunsemi, John McCall, Mathias Kern, Benjamin Lacroix, David Corsar, Gilbert Owusu:
Job Assignment Problem and Traveling Salesman Problem: A Linked Optimisation Problem. SGAI Conf. 2022: 19-33 - [c100]Truong Dang, Tien Thanh Nguyen, John McCall, Alan Wee-Chung Liew:
Ensemble Learning based on Classifier Prediction Confidence and Comprehensive Learning Particle Swarm Optimisation for Medical Image Segmentation. SSCI 2022: 269-276 - [i3]Alexander E. I. Brownlee, Martin Pelikan, John A. W. McCall, Andrei Petrovski:
An Application of a Multivariate Estimation of Distribution Algorithm to Cancer Chemotherapy. CoRR abs/2205.08438 (2022) - 2021
- [c99]Kate Han, Tien Pham, Trung Hieu Vu, Truong Dang, John A. W. McCall, Tien Thanh Nguyen:
VEGAS: A Variable Length-Based Genetic Algorithm for Ensemble Selection in Deep Ensemble Learning. ACIIDS 2021: 168-180 - [c98]Truong Dang, Tien Thanh Nguyen, Carlos Francisco Moreno-García, Eyad Elyan, John A. W. McCall:
Weighted Ensemble of Deep Learning Models based on Comprehensive Learning Particle Swarm Optimization for Medical Image Segmentation. CEC 2021: 744-751 - [c97]Daniel Dobos, Tien Thanh Nguyen, John A. W. McCall, Allan Wilson, Phil Stockton, Helen Corbett:
Weighted ensemble of gross error detection methods based on particle swarm optimization. GECCO Companion 2021: 307-308 - [c96]Kate Han, Lee A. Christie, Alexandru-Ciprian Zavoianu, John McCall:
Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms. GECCO Companion 2021: 315-316 - [c95]Arnaud Liefooghe, Sébastien Vérel, Benjamin Lacroix, Alexandru-Ciprian Zavoianu, John A. W. McCall:
Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems. GECCO 2021: 421-429 - [c94]Joan Alza, Mark Bartlett, Josu Ceberio, John A. W. McCall:
Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem. GECCO Companion 2021: 1405-1413 - [c93]Martin Fyvie, John A. W. McCall, Lee A. Christie:
Towards Explainable Metaheuristics: PCA for Trajectory Mining in Evolutionary Algorithms. SGAI Conf. 2021: 89-102 - [c92]Martin Fyvie, John A. W. McCall, Lee A. Christie:
Non-Deterministic Solvers and Explainable AI through Trajectory Mining. SICSA XAI 2021: 75-78 - [i2]Truong Dang, Tien Thanh Nguyen, John McCall, Eyad Elyan, Carlos Francisco Moreno-García:
Two layer Ensemble of Deep Learning Models for Medical Image Segmentation. CoRR abs/2104.04809 (2021) - [i1]Truong Dang, Tien Thanh Nguyen, John A. W. McCall, Alan Wee-Chung Liew:
Ensemble Learning based on Classifier Prediction Confidence and Comprehensive Learning Particle Swarm Optimisation for polyp localisation. CoRR abs/2104.04832 (2021) - 2020
- [j12]Christopher Brown, Vladimir Janjic, Mehdi Goli, John A. W. McCall:
Programming Heterogeneous Parallel Machines Using Refactoring and Monte-Carlo Tree Search. Int. J. Parallel Program. 48(4): 583-602 (2020) - [j11]Tien Thanh Nguyen, Manh Truong Dang, Vimal Anand Baghel, Anh Vu Luong, John McCall, Alan Wee-Chung Liew:
Evolving interval-based representation for multiple classifier fusion. Knowl. Based Syst. 201-202: 106034 (2020) - [j10]Tien Thanh Nguyen, Anh Vu Luong, Manh Truong Dang, Alan Wee-Chung Liew, John McCall:
Ensemble Selection based on Classifier Prediction Confidence. Pattern Recognit. 100: 107104 (2020) - [c91]Duc Thuan Do, Tien Thanh Nguyen, The Trung Nguyen, Anh Vu Luong, Alan Wee-Chung Liew, John McCall:
Confidence in Prediction: An Approach for Dynamic Weighted Ensemble. ACIIDS (1) 2020: 358-370 - [c90]Reginald Ankrah, Benjamin Lacroix, John A. W. McCall, Andrew Hardwick, Anthony Conway, Gilbert Owusu:
Racing Strategy for the Dynamic-Customer Location-Allocation Problem. CEC 2020: 1-8 - [c89]Ashish Upadhyay, Tien Thanh Nguyen, Stewart Massie, John A. W. McCall:
WEC: Weighted Ensemble of Text Classifiers. CEC 2020: 1-8 - [c88]Tien Thanh Nguyen, John McCall, Allan Wilson, Laud Ochei, Helen Corbett, Phil Stockton:
Evolved ensemble of detectors for gross error detection. GECCO Companion 2020: 281-282 - [c87]Tien Thanh Nguyen, Nang Van Pham, Manh Truong Dang, Anh Vu Luong, John McCall, Alan Wee-Chung Liew:
Multi-layer heterogeneous ensemble with classifier and feature selection. GECCO 2020: 725-733 - [c86]Anh Vu Luong, Trung Hieu Vu, Phuong Minh Nguyen, Nang Van Pham, John A. W. McCall, Alan Wee-Chung Liew, Tien Thanh Nguyen:
A Homogeneous-Heterogeneous Ensemble of Classifiers. ICONIP (5) 2020: 251-259 - [c85]Truong Dang, Tien Thanh Nguyen, John McCall:
Toward an Ensemble of Object Detectors. ICONIP (5) 2020: 458-467 - [c84]Alexandru-Ciprian Zavoianu, Benjamin Lacroix, John McCall:
Comparative Run-Time Performance of Evolutionary Algorithms on Multi-objective Interpolated Continuous Optimisation Problems. PPSN (1) 2020: 287-300 - [c83]Akinola Ogunsemi, John A. W. McCall, Mathias Kern, Benjamin Lacroix, David Corsar, Gilbert Owusu:
Ensemble-Based Relationship Discovery in Relational Databases. SGAI Conf. 2020: 286-300
2010 – 2019
- 2019
- [j9]Tien Thanh Nguyen, Manh Truong Dang, Dung Pham, Lan Phuong Dao, Anh Vu Luong, John McCall, Alan Wee-Chung Liew:
Deep Heterogeneous Ensemble. Aust. J. Intell. Inf. Process. Syst. 16(1): 1-9 (2019) - [j8]Tien Thanh Nguyen, Manh Truong Dang, Anh Vu Luong, Alan Wee-Chung Liew, Tiancai Liang, John McCall:
Multi-label classification via incremental clustering on an evolving data stream. Pattern Recognit. 95: 96-113 (2019) - [c82]Reginald Ankrah, Benjamin Lacroix, John A. W. McCall, Andrew Hardwick, Anthony Conway:
Introducing the Dynamic Customer Location-Allocation Problem. CEC 2019: 3157-3164 - [c81]Tien Thanh Nguyen, Anh Vu Luong, Thi Minh Van Nguyen, Trong Sy Ha, Alan Wee-Chung Liew, John McCall:
Simultaneous meta-data and meta-classifier selection in multiple classifier system. GECCO 2019: 39-46 - [c80]Benjamin Lacroix, John A. W. McCall:
Limitations of benchmark sets and landscape features for algorithm selection and performance prediction. GECCO (Companion) 2019: 261-262 - [c79]Joan Alza, Mark Bartlett, Josu Ceberio, John McCall:
On the definition of dynamic permutation problems under landscape rotation. GECCO (Companion) 2019: 1518-1526 - [c78]Tien Thanh Nguyen, Anh Vu Luong, Manh Truong Dang, Lan Phuong Dao, Thi Thu Thuy Nguyen, Alan Wee-Chung Liew, John McCall:
Evolving an Optimal Decision Template for Combining Classifiers. ICONIP (1) 2019: 608-620 - 2018
- [c77]Russell Ainslie, John A. W. McCall, Sid Shakya, Gilbert Owusu:
Tactical Plan Optimisation for Large Multi-Skilled Workforces Using a Bi-Level Model. CEC 2018: 1-8 - [c76]Reginald Ankrah, Olivier Regnier-Coudert, John A. W. McCall, Anthony Conway, Andrew Hardwick:
Performance Analysis of GA and PBIL Variants for Real-World Location-Allocation Problems. CEC 2018: 1-8 - [c75]Benjamin Lacroix, John A. W. McCall, Jérôme Lonchampt:
Iterated Racing Algorithm for Simulation-Optimisation of Maintenance Planning. CEC 2018: 1-7 - [c74]Charles Neau, Olivier Regnier-Coudert, John A. W. McCall:
An Analysis of Indirect Optimisation Strategies for Scheduling. CEC 2018: 1-8 - [c73]Reginald Ankrah, Benjamin Lacroix, John A. W. McCall, Andrew Hardwick, Anthony Conway:
A Holistic Metric Approach to Solving the Dynamic Location-Allocation Problem. SGAI Conf. 2018: 433-439 - 2017
- [c72]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert:
Estimation of distribution algorithms for the Multi-Mode Resource Constrained Project scheduling problem. CEC 2017: 1579-1586 - [c71]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert, Liam Bowie:
A Random Key based Estimation of Distribution Algorithm for the Permutation Flowshop Scheduling Problem. CEC 2017: 2364-2371 - [c70]Benjamin Lacroix, Lee A. Christie, John A. W. McCall:
Interpolated continuous optimisation problems with tunable landscape features. GECCO (Companion) 2017: 169-170 - [c69]Russell Ainslie, John A. W. McCall, Sid Shakya, Gilbert Owusu:
Predicting Service Levels Using Neural Networks. SGAI Conf. 2017: 411-416 - 2016
- [c68]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert:
BPGA-EDA for the multi-mode resource constrained project scheduling problem. CEC 2016: 3417-3424 - [c67]Peter A. N. Bosman, John A. W. McCall:
GECCO'16 Model-Based Evolutionary Algorithms (MBEA) Workshop Chairs' Welcome. GECCO (Companion) 2016: 1401 - [c66]Russell Ainslie, John A. W. McCall, Siddhartha Shakya, Gilbert Owusu:
Predictive planning with neural networks. IJCNN 2016: 2110-2117 - [c65]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert:
RK-EDA: A Novel Random Key Based Estimation of Distribution Algorithm. PPSN 2016: 849-858 - 2015
- [j7]Claire E. Gerrard, John A. W. McCall, Christopher MacLeod, George M. Coghill:
Applications and design of cooperative multi-agent ARN-based systems. Soft Comput. 19(6): 1581-1594 (2015) - [c64]Prapa Rattadilok, John A. W. McCall, Trevor Burbridge, Andrea Soppera, Philip Eardley:
A data fusion framework for large-scale measurement platforms. IEEE BigData 2015: 2150-2158 - [c63]Alexander E. I. Brownlee, John A. W. McCall, Lee A. Christie:
Structural coherence of problem and algorithm: An analysis for EDAs on all 2-bit and 3-bit problems. CEC 2015: 2066-2073 - [c62]Juan Ignacio Alonso-Barba, Luis de la Ossa, Olivier Regnier-Coudert, John A. W. McCall, José A. Gámez, José Miguel Puerta:
Ant Colony and Surrogate Tree-Structured Models for Orderings-Based Bayesian Network Learning. GECCO 2015: 543-550 - [c61]Mayowa Ayodele, John A. W. McCall, Olivier Regnier-Coudert:
Probabilistic Model Enhanced Genetic Algorithm for Multi-Mode Resource Constrained Project Scheduling Problem. GECCO (Companion) 2015: 745-746 - [c60]John A. W. McCall, Lee A. Christie, Alexander E. I. Brownlee:
Generating Easy and Hard Problems using the Proximate Optimality Principle. GECCO (Companion) 2015: 767-768 - [c59]Russell Ainslie, Siddhartha Shakya, John A. W. McCall, Gilbert Owusu:
Optimising Skill Matching in the Service Industry for Large Multi-skilled Workforces. SGAI Conf. 2015: 231-243 - 2014
- [j6]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
D2MOPSO: MOPSO Based on Decomposition and Dominance with Archiving Using Crowding Distance in Objective and Solution Spaces. Evol. Comput. 22(1): 47-77 (2014) - [j5]Claire E. Gerrard, John A. W. McCall, George Macleod Coghill, Christopher MacLeod:
Exploring aspects of cell intelligence with artificial reaction networks. Soft Comput. 18(10): 1899-1912 (2014) - [c58]Lee A. Christie, John A. W. McCall, David P. Lonie:
Minimal walsh structure and ordinal linkage of monotonicity-invariant function classes on bit strings. GECCO 2014: 333-340 - [c57]Olivier Regnier-Coudert, John A. W. McCall:
Factoradic Representation for Permutation Optimisation. PPSN 2014: 332-341 - 2013
- [j4]Alexander E. I. Brownlee, Olivier Regnier-Coudert, John A. W. McCall, Stewart Massie, Stefan Stulajter:
An application of a GA with Markov network surrogate to feature selection. Int. J. Syst. Sci. 44(11): 2039-2056 (2013) - [j3]Alexander E. I. Brownlee, John A. W. McCall, Qingfu Zhang:
Fitness Modeling With Markov Networks. IEEE Trans. Evol. Comput. 17(6): 862-879 (2013) - [c56]Claire Gerrard, John A. W. McCall, Christopher MacLeod, George Macleod Coghill:
Artificial chemistry approach to exploring search spaces using Artificial Reaction Network agents. IEEE Congress on Evolutionary Computation 2013: 1201-1208 - [c55]Mehdi Goli, John A. W. McCall, Christopher Brown, Vladimir Janjic, Kevin Hammond:
Mapping parallel programs to heterogeneous CPU/GPU architectures using a Monte Carlo Tree Search. IEEE Congress on Evolutionary Computation 2013: 2932-2939 - [c54]Claire E. Gerrard, John A. W. McCall, George M. Coghill, Christopher MacLeod:
Artificial Reaction Network Agents. ECAL 2013: 957-964 - [c53]Olivier Regnier-Coudert, John A. W. McCall, Mayowa Ayodele:
Geometric-based sampling for permutation optimization. GECCO 2013: 399-406 - [c52]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
Mutual Information for Performance Assessment of Multi Objective Optimisers: Preliminary Results. IDEAL 2013: 537-544 - [c51]Claire Gerrard, John A. W. McCall, Christopher MacLeod, George Macleod Coghill:
Combining biochemical network motifs within an ARN-agent control system. UKCI 2013: 8-15 - [c50]Lee A. Christie, David P. Lonie, John A. W. McCall:
Partial structure learning by subset walsh transform. UKCI 2013: 128-135 - [p1]Thierry Mamer, John A. W. McCall, Siddhartha Shakya, Gilbert Owusu, Olivier Regnier-Coudert:
Understanding Team Dynamics with Agent-Based Simulation. Transforming Field and Service Operations 2013: 183-198 - [e1]Gilbert Owusu, Paul O'Brien, John A. W. McCall, Neil F. Doherty:
Transforming Field and Service Operations, Methodologies for Successful Technology-Driven Business Transformation. Springer 2013, ISBN 978-3-642-44969-7 [contents] - 2012
- [j2]Olivier Regnier-Coudert, John A. W. McCall, Robert Lothian, Thomas Lam, Sam McClinton, James N'Dow:
Machine learning for improved pathological staging of prostate cancer: A performance comparison on a range of classifiers. Artif. Intell. Medicine 55(1): 25-35 (2012) - [c49]Noura Al Moubayed, Bashar Awwad Shiekh Hasan, John Q. Gan, Andrei Petrovski, John A. W. McCall:
Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces. IEEE Congress on Evolutionary Computation 2012: 1-7 - [c48]Olivier Regnier-Coudert, John A. W. McCall:
An Island Model Genetic Algorithm for Bayesian network structure learning. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c47]Yanghui Wu, John A. W. McCall, David Corne, Olivier Regnier-Coudert:
Landscape analysis for hyperheuristic Bayesian Network structure learning on unseen problems. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c46]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
D 2 MOPSO: Multi-Objective Particle Swarm Optimizer Based on Decomposition and Dominance. EvoCOP 2012: 75-86 - [c45]Alexander E. I. Brownlee, John A. W. McCall, Martin Pelikan:
Influence of selection on structure learning in markov network EDAs: an empirical study. GECCO 2012: 249-256 - [c44]Claire Gerrard, John A. W. McCall, George Macleod Coghill, Christopher MacLeod:
Temporal Patterns in Artificial Reaction Networks. ICANN (1) 2012: 1-8 - [c43]Claire Gerrard, John A. W. McCall, George Macleod Coghill, Christopher MacLeod:
Adaptive Dynamic Control of Quadrupedal Robotic Gaits with Artificial Reaction Networks. ICONIP (1) 2012: 280-287 - [c42]Olivier Regnier-Coudert, John A. W. McCall:
Competing Mutating Agents for Bayesian Network Structure Learning. PPSN (1) 2012: 216-225 - 2011
- [c41]Yanghui Wu, John A. W. McCall, David Corne:
Fitness landscape analysis of Bayesian network structure learning. IEEE Congress on Evolutionary Computation 2011: 981-988 - [c40]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
Multi-objective optimisation of cancer chemotherapy using smart PSO with decomposition. MCDM 2011: 81-88 - [c39]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
Clustering based leaders' selection in multi-objective evolutionary algorithms. GECCO (Companion) 2011: 95-96 - [c38]Olivier Regnier-Coudert, John A. W. McCall:
Privacy-preserving approach to bayesian network structure learning from distributed data. GECCO (Companion) 2011: 815-816 - [c37]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
Clustering-Based Leaders' Selection in Multi-Objective Particle Swarm Optimisation. IDEAL 2011: 100-107 - [c36]Thierry Mamer, Siddhartha Shakya, John A. W. McCall, Gilbert Owusu:
Intelligent Tuning of a Dynamic Business Simulation Environment. SGAI Conf. 2011: 355-368 - 2010
- [c35]Robert Barbour, David W. Corne, John A. W. McCall:
Accelerated optimisation of chemotherapy dose schedules using fitness inheritance. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c34]Alexander E. I. Brownlee, Olivier Regnier-Coudert, John A. W. McCall, Stewart Massie:
Using a Markov network as a surrogate fitness function in a genetic algorithm. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c33]François A. Fournier, John A. W. McCall, Andrei Petrovski, Peter J. Barclay:
Evolved Bayesian Network models of rig operations in the gulf of Mexico. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c32]Jean-Claude Golovine, John A. W. McCall, Patrik O'Brian Holt:
Evolving interface designs to minimize user task times as simulated in a cognitive architecture. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c31]Yanghui Wu, John A. W. McCall, David W. Corne:
Two novel Ant Colony Optimization approaches for Bayesian network structure learning. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c30]Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
A Novel Smart Multi-Objective Particle Swarm Optimisation Using Decomposition. PPSN (2) 2010: 1-10 - [c29]Yanghui Wu, John A. W. McCall, David Corne:
Comparative Analysis of Search and Score Metaheuristics for Bayesian Network Structure Learning Using Node Juxtaposition Distributions. PPSN (1) 2010: 424-433
2000 – 2009
- 2009
- [c28]Alexander E. I. Brownlee, John A. W. McCall, Siddhartha Shakya, Qingfu Zhang:
Structure learning and optimisation in a Markov-network based estimation of distribution algorithm. IEEE Congress on Evolutionary Computation 2009: 447-454 - [c27]Siddhartha Shakya, Alexander E. I. Brownlee, John A. W. McCall, François A. Fournier, Gilbert Owusu:
A fully multivariate DEUM algorithm. IEEE Congress on Evolutionary Computation 2009: 479-486 - 2008
- [c26]Paul Michael Godley, Julie Cowie, David E. Cairns, John A. W. McCall, C. Howie:
Optimisation of cancer chemotherapy schedules using directed intervention crossover approaches. IEEE Congress on Evolutionary Computation 2008: 2532-2537 - [c25]Alexander E. I. Brownlee, John A. W. McCall, Qingfu Zhang, Deryck Forsyth Brown:
Approaches to selection and their effect on fitness modelling in an Estimation of Distribution Algorithm. IEEE Congress on Evolutionary Computation 2008: 2621-2628 - [c24]Yanghui Wu, John A. W. McCall, Paul Michael Godley, Alexander E. I. Brownlee, David E. Cairns, Julie Cowie:
Bio-control in mushroom farming using a Markov network EDA. IEEE Congress on Evolutionary Computation 2008: 2991-2996 - [c23]Paul Michael Godley, David E. Cairns, Julie Cowie, John A. W. McCall:
Fitness directed intervention crossover approaches applied to bio-scheduling problems. CIBCB 2008: 120-127 - [c22]David W. Archer, Lois M. L. Delcambre, Fabio Corubolo, Lillian N. Cassel, Susan Price, Uma Murthy, David Maier, Edward A. Fox, Sudarshan Murthy, John A. W. McCall, Kiran Kuchibhotla, Rahul Suryavanshi:
Superimposed Information Architecture for Digital Libraries. ECDL 2008: 88-99 - [c21]Alexander E. I. Brownlee, Martin Pelikan, John A. W. McCall, Andrei Petrovski:
An application of a multivariate estimation of distribution algorithm to cancer chemotherapy. GECCO 2008: 463-464 - [c20]Alexander E. I. Brownlee, Yanghui Wu, John A. W. McCall, Paul Michael Godley, David E. Cairns, Julie Cowie:
Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network eda. GECCO 2008: 465-466 - [c19]Paul Michael Godley, David E. Cairns, Julie Cowie, Kevin Swingler, John A. W. McCall:
The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy. GECCO 2008: 1105-1106 - [c18]Ratiba Kabli, John A. W. McCall, Frank Herrmann, Eng Ong:
Evolved bayesian networks as a versatile alternative to partin tables for prostate cancer management. GECCO 2008: 1547-1554 - [c17]Thierry Mamer, Christopher H. Bryant, John A. W. McCall:
L-Modified ILP Evaluation Functions for Positive-Only Biological Grammar Learning. ILP 2008: 176-191 - 2007
- [j1]Siddhartha Shakya, John A. W. McCall:
Optimization by estimation of distribution with DEUM framework based on Markov random fields. Int. J. Autom. Comput. 4(3): 262-272 (2007) - [c16]Ratiba Kabli, Frank Herrmann, John A. W. McCall:
A chain-model genetic algorithm for Bayesian network structure learning. GECCO 2007: 1264-1271 - [c15]Alexander E. I. Brownlee, John A. W. McCall, Deryck Forsyth Brown:
Solving the MAXSAT problem using a multivariate EDA based on Markov networks. GECCO (Companion) 2007: 2423-2428 - 2006
- [c14]Siddhartha Shakya, John A. W. McCall, Deryck Forsyth Brown:
Solving the Ising Spin Glass Problem using a Bivariate EDA based on Markov Random Fields. IEEE Congress on Evolutionary Computation 2006: 908-915 - [c13]Andrei Petrovski, Siddhartha Shakya, John A. W. McCall:
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms. GECCO 2006: 413-418 - 2005
- [c12]Andrei Petrovski, Alexander E. I. Brownlee, John A. W. McCall:
Statistical optimisation and tuning of GA factors. Congress on Evolutionary Computation 2005: 758-764 - [c11]Siddhartha Shakya, John A. W. McCall, Deryck Forsyth Brown:
Incorporating a Metropolis method in a distribution estimation using Markov random field algorithm. Congress on Evolutionary Computation 2005: 2576-2583 - [c10]Andrei Petrovski, John A. W. McCall:
Smart problem solving environment for medical decision support. GECCO Workshops 2005: 152-158 - [c9]Siddhartha Shakya, John A. W. McCall, Deryck Forsyth Brown:
Using a Markov network model in a univariate EDA: an empirical cost-benefit analysis. GECCO 2005: 727-734 - 2004
- [c8]Andrei Petrovski, Bhavani Sudha, John A. W. McCall:
Optimising Cancer Chemotherapy Using Particle Swarm Optimisation and Genetic Algorithms. PPSN 2004: 633-641 - 2003
- [c7]Hayet Farida Merouani, John A. W. McCall, Ian McKenzie, Fiona J. Gilbert:
Classification of GRF texture in mammograms through discriminant analysis. ISSPA (1) 2003: 673-676 - 2001
- [c6]Deryck Forsyth Brown, A. Beatriz Garmendia-Doval, John A. W. McCall:
Markov Random Field Modelling of Royal Road Genetic Algorithms. Artificial Evolution 2001: 65-76 - [c5]Andrei Petrovski, John A. W. McCall:
Multi-objective Optimisation of Cancer Chemotherapy Using Evolutionary Algorithms. EMO 2001: 531-545 - 2000
- [c4]Deryck Forsyth Brown, S. J. Cuddy, A. Beatriz Garmendia-Doval, John A. W. McCall:
The Prediction of Permeability in Oil-Bearing Strata using Genetic Algorithms. Artificial Intelligence and Soft Computing 2000: 53-57 - [c3]Stewart Thomson, John A. W. McCall, David Crossen:
Component Based Visual Software Engineering. ICEIS 2000: 363-367 - [c2]Deryck Forsyth Brown, A. Beatriz Garmendia-Doval, John A. W. McCall:
A functional framework for the implementation of genetic algorithms: Comparing Haskell and Standard ML. Scottish Functional Programming Workshop 2000: 27-38
1990 – 1999
- 1999
- [c1]Stewart Thomson, John A. W. McCall:
Towards a Visual Environment for Enterprise Systems. ICEIS 1999: 774
Coauthor Index
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