publications

2024

1. Re-Identification of Individual Kākā: An Explainable DINO-Based Model

   Paula Maddigan, Oskar Ehrhardt, Andrew Lensen, and Rachael C. Shaw

   In Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ), Dec 2024

   To Appear

   Bib PDF

   @inproceedings{maddigan2024reidentification,
     author = {Maddigan, Paula and Ehrhardt, Oskar and Lensen, Andrew and Shaw, {Rachael C.}},
     title = {Re-Identification of Individual Kākā: An Explainable {DINO}-Based Model},
     booktitle = {Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ)},
     year = {2024},
     month = dec,
     day = {4},
     publisher = {{IEEE}},
     note = {To Appear}
   }

2. Interpretable Local Explanations Through Genetic Programming

   Hayden Andersen, Andrew Lensen, Will N. Browne, and Yi Mei

   In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, Jul 2024

   Bib PDF DOI

   @inproceedings{andersen2024interpretable,
     author = {Andersen, Hayden and Lensen, Andrew and Browne, {Will N.} and Mei, Yi},
     title = {Interpretable Local Explanations Through Genetic Programming},
     booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion},
     year = {2024},
     month = jul,
     day = {14},
     publisher = {{ACM}},
     doi = {10.1145/3638530.3654370},
     pages = {247--250},
   }

3. Explaining Genetic Programming Trees using Large Language Models

   Paula Maddigan, Andrew Lensen, and Bing Xue

   arXiv, Mar 2024

   Bib PDF DOI

   @article{maddigan2024explaining,
     author = {Maddigan, Paula and Lensen, Andrew and Xue, Bing},
     title = {Explaining Genetic Programming Trees using Large Language Models},
     year = {2024},
     doi = {10.48550/arXiv.2403.03397},
     eprinttype = {arXiv},
     eprint = {2403.03397},
     journal = {arXiv},
     month = mar,
     day = {6},
   }

4. Genetic Programming Trees for Explainable Manifold Learning

   Ben Cravens, Andrew Lensen, Paula Maddigan, and Bing Xue

   arXiv, Mar 2024

   Bib PDF DOI

   @article{cravens2024genetic,
     author = {Cravens, Ben and Lensen, Andrew and Maddigan, Paula and Xue, Bing},
     title = {Genetic Programming Trees for Explainable Manifold Learning},
     year = {2024},
     doi = {10.48550/arXiv.2403.14139},
     eprinttype = {arXiv},
     eprint = {2403.14139},
     journal = {arXiv},
     month = mar,
     day = {22},
   }

2023

1. Explainable Artificial Intelligence by Genetic Programming: A Survey

   Yi Mei, Qi Chen, Andrew Lensen, Bing Xue, and Mengjie Zhang

   IEEE Transactions on Evolutionary Computation, Nov 2023

   Bib PDF DOI

   @article{mei2022explainable,
     author = {Mei, Yi and Chen, Qi and Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Explainable Artificial Intelligence by Genetic Programming: A Survey},
     journal = {{IEEE} Transactions on Evolutionary Computation},
     pages = {621--641},
     year = {2023},
     volume = {27},
     number = {3},
     month = nov,
     day = {25},
     publisher = {IEEE},
     doi = {10.1109/TEVC.2022.3225509},
   }

2. Explainable AI–building trust through understanding

   Matt Lythe, Gabriella Mazorra Cos, Maria Mingallon, Andrew Lensen, Christopher Galloway, David Knox, Sarah Auvaa, and Kaushalya Kumarasinghe

   Nov 2023

   Bib PDF

   @article{lythe2023explainable,
     title = {Explainable AI--building trust through understanding},
     author = {Lythe, Matt and de Cos, Gabriella Mazorra and Mingallon, Maria and Lensen, Andrew and Galloway, Christopher and Knox, David and Auvaa, Sarah and Kumarasinghe, Kaushalya},
     year = {2023},
     month = nov,
     publisher = {AI Forum New Zealand},
   }

3. Producing Diverse Rashomon Sets of Counterfactual Explanations with Niching Particle Swarm Optimisation

   Hayden Andersen, Andrew Lensen, Will N. Browne, and Yi Mei

   In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), Jul 2023

   Bib PDF DOI

   @inproceedings{andersen2023producing,
     author = {Andersen, Hayden and Lensen, Andrew and Browne, {Will N.} and Mei, Yi},
     title = {Producing Diverse Rashomon Sets of Counterfactual Explanations with Niching Particle Swarm Optimisation},
     booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)},
     year = {2023},
     month = jul,
     day = {15},
     publisher = {{ACM}},
     pages = {393--401},
     doi = {10.1145/3583131.3590444}
   }

4. A Genetic Programming Encoder for Increasing Autoencoder Interpretability

   Finn Schofield, Luis Slyfield, and Andrew Lensen

   In Proceedings of the European Conference on Genetic Programming (EuroGP), Apr 2023

   Bib PDF DOI

   @inproceedings{schofield2023genetic,
     author = {Schofield, Finn and Slyfield, Luis and Lensen, Andrew},
     title = {A Genetic Programming Encoder for Increasing Autoencoder Interpretability},
     booktitle = {Proceedings of the European Conference on Genetic Programming (EuroGP)},
     year = {2023},
     month = apr,
     day = {12},
     volume = {13986},
     series = {Lecture Notes in Computer Science},
     publisher = {Springer},
     pages = {19--35},
     doi = {10.1007/978-3-031-29573-7_2}
   }

5. Differentiable Genetic Programming for High-dimensional Symbolic Regression

   Peng Zeng, Xiaotian Song, Andrew Lensen, Yuwei Ou, Yanan Sun, Mengjie Zhang, and Jiancheng Lv

   arXiv, Apr 2023

   Bib PDF DOI

   @article{zeng2023differentiable,
     author = {Zeng, Peng and Song, Xiaotian and Lensen, Andrew and Ou, Yuwei and Sun, Yanan and Zhang, Mengjie and Lv, Jiancheng},
     title = {Differentiable Genetic Programming for High-dimensional Symbolic Regression},
     year = {2023},
     doi = {10.48550/arXiv.2304.08915},
     eprinttype = {arXiv},
     eprint = {2304.08915},
     journal = {arXiv},
     month = apr,
     day = {18},
   }

6. Feature-based Image Matching for Identifying Individual Kākā

   Fintan O’Sullivan, Kirita-Rose Escott, Rachael C. Shaw, and Andrew Lensen

   arXiv, Jan 2023

   Bib PDF DOI

   @article{osullivan2023feature,
     author = {O'Sullivan, Fintan and Escott, Kirita{-}Rose and Shaw, {Rachael C.} and Lensen, Andrew},
     title = {Feature-based Image Matching for Identifying Individual Kākā},
     year = {2023},
     doi = {10.48550/arXiv.2301.06678},
     eprinttype = {arXiv},
     eprint = {2301.06678},
     journal = {arXiv},
     month = jan,
     day = {17},
   }

2022

1. Using Neural Networks to Automate Monitoring of Fish Stocks

   Michael Stanley, Andrew Lensen, and Mengjie Zhang

   In Proceedings of the Symposium Series on Computational Intelligence (SSCI), Dec 2022

   Bib PDF DOI

   @inproceedings{stanley2022using,
     author = {Stanley, Michael and Lensen, Andrew and Zhang, Mengjie},
     title = {Using Neural Networks to Automate Monitoring of Fish Stocks
                      },
     booktitle = {Proceedings of the Symposium Series on Computational Intelligence (SSCI)},
     year = {2022},
     month = dec,
     day = {4},
     pages = {1--6},
     publisher = {{IEEE}},
     doi = {10.1109/SSCI51031.2022.10022081}
   }

2. Speeding up Genetic Programming Based Symbolic Regression Using GPUs

   Rui Zhang, Andrew Lensen, and Yanan Sun

   In Proceedings of the Pacific Rim International Conference on Artificial Intelligence (PRICAI), Nov 2022

   Bib PDF DOI

   @inproceedings{zhang2022speeding,
     author = {Zhang, Rui and Lensen, Andrew and Sun, Yanan},
     title = {Speeding up Genetic Programming Based Symbolic Regression Using GPUs},
     booktitle = {Proceedings of the  Pacific Rim International Conference on Artificial Intelligence  (PRICAI)},
     year = {2022},
     month = nov,
     day = {10},
     pages = {1--14},
     publisher = {{IEEE}},
     doi = {10.1007/978-3-031-20862-1_38}
   }

3. Genetic Programming for Manifold Learning: Preserving Local Topology

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   IEEE Transactions on Evolutionary Computation, Aug 2022

   Bib PDF DOI

   @article{lensen2021genetic,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Genetic Programming for Manifold Learning: Preserving Local Topology},
     journal = {{IEEE} Transactions on Evolutionary Computation},
     pages = {661--675},
     year = {2022},
     month = aug,
     day = {23},
     volume = {26},
     number = {4},
     publisher = {IEEE},
     doi = {10.1109/TEVC.2021.3106672}
   }

4. Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand

   Harry Rodger, Andrew Lensen, and Marcin Betkier

   Journal of the Royal Society of New Zealand, Aug 2022

   Bib PDF DOI

   @article{rodger2022explainable,
     author = {Rodger, Harry and Lensen, Andrew and Betkier, Marcin},
     title = {Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand},
     journal = {Journal of the Royal Society of New Zealand},
     year = {2022},
     month = aug,
     pages = {1--15},
     day = {15},
     publisher = {Taylor & Francis},
     doi = {10.1080/03036758.2022.2114506},
   }

5. Large Scale Image Classification Using GPU-based Genetic Programming

   Peng Zeng, Andrew Lensen, and Yanan Sun

   In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, Jul 2022

   Bib PDF DOI

   @inproceedings{zeng2022large,
     author = {Zeng, Peng and Lensen, Andrew and Sun, Yanan},
     title = {Large Scale Image Classification Using {GPU}-based Genetic Programming},
     booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion},
     year = {2022},
     month = jul,
     day = {9},
     pages = {619--622},
     publisher = {{ACM}},
     doi = {10.1145/3520304.3528892}
   }

6. Improving the Search of Learning Classifier Systems Through Interpretable Feature Clustering

   Hayden Andersen, Andrew Lensen, and Will N. Browne

   In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, Jul 2022

   Bib PDF DOI

   @inproceedings{andersen2022improving,
     author = {Andersen, Hayden and Lensen, Andrew and Browne, {Will N.}},
     title = {Improving the Search of Learning Classifier Systems Through Interpretable Feature Clustering},
     booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion},
     year = {2022},
     month = jul,
     day = {9},
     pages = {1752--1756},
     publisher = {{ACM}},
     doi = {10.1145/3520304.3534027}
   }

7. Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution

   Hayden Andersen, Andrew Lensen, Will N. Browne, and Yi Mei

   In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Jul 2022

   Bib PDF DOI

   @inproceedings{andersen2022evolving,
     author = {Andersen, Hayden and Lensen, Andrew and Browne, {Will N.} and Mei, Yi},
     title = {Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution},
     booktitle = {Proceedings of the {IEEE} Congress on Evolutionary Computation (CEC)},
     year = {2022},
     month = jul,
     day = {18},
     pages = {1--8},
     publisher = {{IEEE}},
     doi = {10.1109/CEC55065.2022.9870283}
   }

2021

1. Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   IEEE Transactions on Cybernetics, Nov 2021

   Bib PDF DOI

   @article{lensen2020genetic,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation},
     journal = {{IEEE} Transactions on Cybernetics},
     pages = {5468--5482},
     year = {2021},
     month = nov,
     day = {9},
     volume = {51},
     number = {11},
     publisher = {IEEE},
     doi = {10.1109/TCYB.2020.2970198}
   }

2. Genetic Programming for Evolving Similarity Functions Tailored to Clustering Algorithms

   Hayden Andersen, Andrew Lensen, and Bing Xue

   In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Jun 2021

   Bib PDF DOI

   @inproceedings{andersen2021genetic,
     author = {Andersen, Hayden and Lensen, Andrew and Xue, Bing},
     title = {Genetic Programming for Evolving Similarity Functions Tailored to Clustering Algorithms},
     booktitle = {Proceedings of the {IEEE} Congress on Evolutionary Computation (CEC)},
     year = {2021},
     month = jun,
     day = {28},
     publisher = {{IEEE}},
     pages = {688--695},
     doi = {10.1109/CEC45853.2021.9504855}
   }

3. Using Genetic Programming to Find Functional Mappings for UMAP Embeddings

   Finn Schofield, and Andrew Lensen

   In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Jun 2021

   Bib PDF DOI

   @inproceedings{schofield2021using,
     author = {Schofield, Finn and Lensen, Andrew},
     title = {Using Genetic Programming to Find Functional Mappings for UMAP Embeddings},
     booktitle = {Proceedings of the {IEEE} Congress on Evolutionary Computation (CEC)},
     year = {2021},
     month = jun,
     day = {28},
     publisher = {{IEEE}},
     pages = {704--711},
     doi = {10.1109/CEC45853.2021.9504848}
   }

4. Mining Feature Relationships in Data

   Andrew Lensen

   In Proceedings of the European Conference on Genetic Programming (EuroGP), Apr 2021

   Bib PDF DOI

   @inproceedings{lensen2021mining,
     author = {Lensen, Andrew},
     title = {Mining Feature Relationships in Data},
     booktitle = {Proceedings of the European Conference on Genetic Programming (EuroGP)},
     year = {2021},
     month = apr,
     day = {7},
     volume = {12691},
     series = {Lecture Notes in Computer Science},
     publisher = {Springer},
     pages = {247--262},
     doi = {10.1007/978-3-030-72812-0_16}
   }

2020

1. Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   Evolutionary Computation, Dec 2020

   Bib PDF DOI

   @article{lensen2019genetic,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis},
     journal = {Evolutionary Computation},
     volume = {28},
     number = {4},
     pages = {531--561},
     year = {2020},
     month = dec,
     day = {1},
     publisher = {MIT Press},
     doi = {10.1162/evco_a_00264}
   }

2. Evolving Simpler Constructed Features for Clustering Problems with Genetic Programming

   Finn Schofield, and Andrew Lensen

   In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Jul 2020

   Bib PDF DOI

   @inproceedings{schofield2020evolving,
     author = {Schofield, Finn and Lensen, Andrew},
     title = {Evolving Simpler Constructed Features for Clustering Problems with Genetic Programming},
     booktitle = {Proceedings of the {IEEE} Congress on Evolutionary Computation (CEC)},
     year = {2020},
     month = jul,
     day = {19},
     publisher = {{IEEE}},
     pages = {1--8},
     doi = {10.1109/CEC48606.2020.9185575}
   }

3. Multi-Objective Genetic Programming for Manifold Learning: Balancing Quality and Dimensionality

   Andrew Lensen, Mengjie Zhang, and Bing Xue

   Genetic Programming and Evolvable Machines, Feb 2020

   Bib PDF DOI

   @article{lensen2019multi,
     author = {Lensen, Andrew and Zhang, Mengjie and Xue, Bing},
     title = {Multi-Objective Genetic Programming for Manifold Learning: Balancing Quality and Dimensionality},
     journal = {Genetic Programming and Evolvable Machines},
     volume = {21},
     number = {3},
     pages = {399--431},
     year = {2020},
     month = feb,
     day = {5},
     publisher = {Springer},
     doi = {10.1007/s10710-020-09375-4}
   }

2019

1. Evolutionary Feature Manipulation in Unsupervised Learning

   Andrew Lensen

   Sep 2019

   Bib PDF DOI

   @phdthesis{lensen2019thesis,
     author = {Lensen, Andrew},
     title = {Evolutionary Feature Manipulation in Unsupervised Learning},
     year = {2019},
     month = sep,
     pages = {268},
     institution = {Te Herenga Waka---Victoria University of Wellington},
     doi = {10.26686/wgtn.17142221.v1}
   }

2. Can Genetic Programming Do Manifold Learning Too?

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the European Conference on Genetic Programming (EuroGP), Apr 2019

   Best paper

   Bib PDF DOI

   @inproceedings{lensen2019can,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Can Genetic Programming Do Manifold Learning Too?},
     booktitle = {Proceedings of the European Conference on Genetic Programming (EuroGP)},
     year = {2019},
     month = apr,
     day = {24},
     volume = {11451},
     series = {Lecture Notes in Computer Science},
     publisher = {Springer},
     pages = {114--130},
     note = {Best paper},
     doi = {10.1007/978-3-030-16670-0_8}
   }

3. A survey on evolutionary machine learning

   Harith Al-Sahaf, Ying Bi, Qi Chen, Andrew Lensen, Yi Mei, Yanan Sun, Binh Tran, Bing Xue, and Mengjie Zhang

   Journal of the Royal Society of New Zealand, Apr 2019

   Bib PDF DOI

   @article{alsahaf2019survey,
     author = {Al-Sahaf, Harith and Bi, Ying and Chen, Qi and Lensen, Andrew and Mei, Yi and Sun, Yanan and Tran, Binh and Xue, Bing and Zhang, Mengjie},
     title = {A survey on evolutionary machine learning},
     journal = {Journal of the Royal Society of New Zealand},
     volume = {49},
     number = {2},
     pages = {205-228},
     year = {2019},
     month = apr,
     day = {15},
     publisher = {Taylor & Francis},
     doi = {10.1080/03036758.2019.1609052}
   }

2018

1. Automatically Evolving Difficult Benchmark Feature Selection Datasets with Genetic Programming

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), Jul 2018

   Bib PDF DOI

   @inproceedings{lensen2018automatically,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Automatically Evolving Difficult Benchmark Feature Selection Datasets with Genetic Programming},
     booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)},
     pages = {458--465},
     year = {2018},
     month = jul,
     day = {15},
     publisher = {{ACM}},
     doi = {10.1145/3205455.3205552}
   }

2. Particle Swarm Optimisation for Feature Selection and Weighting in High-Dimensional Clustering

   Damien O’Neill, Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Jul 2018

   Bib PDF DOI

   @inproceedings{oneill2018particle,
     author = {O'Neill, Damien and Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Particle Swarm Optimisation for Feature Selection and Weighting in High-Dimensional Clustering},
     booktitle = {Proceedings of the {IEEE} Congress on Evolutionary Computation (CEC)},
     year = {2018},
     month = jul,
     day = {8},
     publisher = {{IEEE}},
     pages = {1--8},
     doi = {10.1109/CEC.2018.8477974}
   }

3. Generating Redundant Features with Unsupervised Multi-tree Genetic Programming

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the European Conference on Genetic Programming (EuroGP), Apr 2018

   Bib PDF DOI

   @inproceedings{lensen2018generating,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Generating Redundant Features with Unsupervised Multi-tree Genetic
                      Programming},
     booktitle = {Proceedings of the European Conference on Genetic Programming (EuroGP)},
     pages = {84--100},
     year = {2018},
     month = apr,
     day = {4},
     series = {Lecture Notes in Computer Science},
     volume = {10781},
     publisher = {Springer},
     doi = {10.1007/978-3-319-77553-1_6},
   }

2017

1. New Representations in Genetic Programming for Feature Construction in k-Means Clustering

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the 11th International Conference on Simulated Evolution and Learning (SEAL), Nov 2017

   Bib PDF DOI

   @inproceedings{lensen2017New,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {New Representations in Genetic Programming for Feature Construction in k-Means Clustering},
     booktitle = {Proceedings of the 11th International Conference on Simulated Evolution and Learning ({SEAL})},
     year = {2017},
     month = nov,
     day = {10},
     volume = {10593},
     series = {Lecture Notes in Computer Science},
     pages = {543--555},
     publisher = {Springer},
     doi = {10.1007/978-3-319-68759-9_44},
   }

2. GPGC: genetic programming for automatic clustering using a flexible non-hyper-spherical graph-based approach

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), Jul 2017

   Bib PDF DOI

   @inproceedings{lensen2017GPGC,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {{GPGC:} genetic programming for automatic clustering using a flexible non-hyper-spherical graph-based approach},
     booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)},
     year = {2017},
     month = jul,
     day = {15},
     pages = {449--456},
     publisher = {{ACM}},
     doi = {10.1145/3071178.3071222},
   }

3. Improving k-means clustering with genetic programming for feature construction

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, Apr 2017

   Bib PDF DOI

   @inproceedings{lensen2017Improving,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Improving {k}-means clustering with genetic programming for feature construction},
     booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion},
     year = {2017},
     month = apr,
     day = {19},
     pages = {237--238},
     publisher = {{ACM}},
     doi = {10.1145/3067695.3075962},
   }

4. Using Particle Swarm Optimisation and the Silhouette Metric to Estimate the Number of Clusters, Select Features, and Perform Clustering

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the European Conference on the Applications of Evolutionary Computation (EvoApplications), Part I, Apr 2017

   Bib PDF DOI

   @inproceedings{lensen2017Using,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Using Particle Swarm Optimisation and the Silhouette Metric to Estimate the Number of Clusters, Select Features, and Perform Clustering},
     booktitle = {Proceedings of the European Conference on the Applications of Evolutionary Computation (EvoApplications), Part {I}},
     year = {2017},
     month = apr,
     day = {19},
     volume = {10199},
     series = {Lecture Notes in Computer Science},
     pages = {538--554},
     publisher = {Springer},
     doi = {10.1007/978-3-319-55849-3_35},
   }

2016

1. Particle Swarm Optimisation Representations for Simultaneous Clustering and Feature Selection

   Andrew Lensen, Bing Xue, and Mengjie Zhang

   In Proceedings of the Symposium Series on Computational Intelligence (SSCI), Dec 2016

   Bib PDF DOI

   @inproceedings{lensen2016Particle,
     author = {Lensen, Andrew and Xue, Bing and Zhang, Mengjie},
     title = {Particle Swarm Optimisation Representations for Simultaneous Clustering and Feature Selection},
     booktitle = {Proceedings of the Symposium Series on Computational Intelligence (SSCI)},
     year = {2016},
     month = dec,
     day = {6},
     pages = {1--8},
     publisher = {{IEEE}},
     doi = {10.1109/SSCI.2016.7850124},
   }

2. Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data

   Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, and Bing Xue

   In Proceedings of the European Conference on Genetic Programming (EuroGP), Mar 2016

   Bib PDF DOI

   @inproceedings{lensen2016Genetic,
     author = {Lensen, Andrew and Al{-}Sahaf, Harith and Zhang, Mengjie and Xue, Bing},
     title = {Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data},
     booktitle = {Proceedings of the European Conference on Genetic Programming (EuroGP)},
     year = {2016},
     month = mar,
     day = {30},
     volume = {9594},
     series = {Lecture Notes in Computer Science},
     pages = {51--67},
     publisher = {Springer},
     doi = {10.1007/978-3-319-30668-1_4},
   }

2015

1. A hybrid Genetic Programming approach to feature detection and image classification

   Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, and Bing Xue

   In Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ), Nov 2015

   Bib PDF DOI

   @inproceedings{lensen2015hybrid,
     author = {Lensen, Andrew and Al{-}Sahaf, Harith and Zhang, Mengjie and Xue, Bing},
     title = {A hybrid Genetic Programming approach to feature detection and image classification},
     booktitle = {Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ)},
     year = {2015},
     month = nov,
     day = {23},
     pages = {1--6},
     publisher = {{IEEE}},
     doi = {10.1109/IVCNZ.2015.7761564},
   }

2. Genetic Programming for algae detection in river images

   Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, and Brijesh Verma

   In Proceedings of the IEEE Congress on Evolutionary Computation (CEC), May 2015

   Bib PDF DOI

   @inproceedings{lensen2015Genetic,
     author = {Lensen, Andrew and Al{-}Sahaf, Harith and Zhang, Mengjie and Verma, Brijesh},
     title = {Genetic Programming for algae detection in river images},
     booktitle = {Proceedings of the {IEEE} Congress on Evolutionary Computation (CEC)},
     year = {2015},
     month = may,
     day = {25},
     pages = {2468--2475},
     publisher = {{IEEE}},
     doi = {10.1109/CEC.2015.7257191},
   }