Published in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2023
Recommended citation: Hayden Andersen, Andrew Lensen, Will N. Browne, Yi Mei, "Producing Diverse Rashomon Sets of Counterfactual Explanations with Niching Particle Swarm Optimisation." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2023. To Appear..
Published in arXiv, 2023
Recommended citation: Peng Zeng, Xiaotian Song, Andrew Lensen, Yuwei Ou, Yanan Sun, Mengjie Zhang, Jiancheng Lv, "Differentiable Genetic Programming for High-dimensional Symbolic Regression." arXiv, 2023. https://doi.org/10.48550/arXiv.2304.08915.
Published in Proceedings of the European Conference on Genetic Programming (EuroGP), 2023
Recommended citation: Finn Schofield, Andrew Lensen, Luis Slyfield, "A Genetic Programming Encoder for Increasing Autoencoder Interpretability." Proceedings of the European Conference on Genetic Programming (EuroGP), 2023. To Appear.
Published in arXiv, 2023
Recommended citation: Fintan O'Sullivan, Kirita-Rose Escott, Rachael Shaw, Andrew Lensen, "Feature-based Image Matching for Identifying Individual Kākā." arXiv, 2023. https://doi.org/10.48550/arXiv.2301.06678.
Published in Proceedings of the Symposium Series on Computational Intelligence (SSCI), 2022
Recommended citation: Michael Stanley, Andrew Lensen, Mengjie Zhang, "Using Neural Networks to Automate Monitoring of Fish Stocks." Proceedings of the Symposium Series on Computational Intelligence (SSCI), 2022.
Published in IEEE Transactions on Evolutionary Computation, 2022
Recommended citation: Yi Mei, Qi Chen, Andrew Lensen, Bing Xue, Mengjie Zhang, "Explainable Artificial Intelligence by Genetic Programming: A Survey." IEEE Transactions on Evolutionary Computation, 2022. Early Access.
Published in Proceedings of the Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2022
Recommended citation: Rui Zhang, Andrew Lensen, Yanan Sun, "Speeding up Genetic Programming Based Symbolic Regression Using GPUs." Proceedings of the Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2022.
Published in IEEE Transactions on Evolutionary Computation, 2022
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Genetic Programming for Manifold Learning: Preserving Local Topology." IEEE Transactions on Evolutionary Computation, 2022.
Published in Journal of the Royal Society of New Zealand, 2022
Recommended citation: Harry Rodger, Andrew Lensen, Marcin Betkier, "Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand." Journal of the Royal Society of New Zealand, 2022. doi: 10.1080/03036758.2022.2114506.
Published in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2022
Recommended citation: Hayden Andersen, Andrew Lensen, Will N. Browne, Yi Mei, "Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2022.
Published in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2022
Recommended citation: Peng Zeng, Andrew Lensen, Yanan Sun, "Large Scale Image Classification Using GPU-based Genetic Programming." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2022.
Published in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2022
Recommended citation: Hayden Andersen, Andrew Lensen, Will N. Browne, "Improving the Search of Learning Classifier Systems Through Interpretable Feature Clustering." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2022.
Published in IEEE Transactions on Cybernetics, 2021
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation." IEEE Transactions on Cybernetics, 2021.
Published in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2021
Recommended citation: Finn Schofield, Andrew Lensen, "Using Genetic Programming to Find Functional Mappings for UMAP Embeddings." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2021.
Published in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2021
Recommended citation: Hayden Andersen, Andrew Lensen, Bing Xue, "Genetic Programming for Evolving Similarity Functions Tailored to Clustering Algorithms." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2021.
Published in Proceedings of the European Conference on Genetic Programming (EuroGP), 2021
Recommended citation: Andrew Lensen, "Mining Feature Relationships in Data." Proceedings of the European Conference on Genetic Programming (EuroGP), 2021.
Published in Evolutionary Computation, 2020
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis." Evolutionary Computation, 2020.
Published in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2020
Recommended citation: Finn Schofield, Andrew Lensen, "Evolving Simpler Constructed Features for Clustering Problems with Genetic Programming." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2020.
Published in Genetic Programming and Evolvable Machines, 2020
Recommended citation: Andrew Lensen, Mengjie Zhang, Bing Xue, "Multi-Objective Genetic Programming for Manifold Learning: Balancing Quality and Dimensionality." Genetic Programming and Evolvable Machines, 2020.
Published in , 2019
Recommended citation: Andrew Lensen, "Evolutionary Feature Manipulation in Unsupervised Learning." , 2019.
Published in Proceedings of the European Conference on Genetic Programming (EuroGP), 2019
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Can Genetic Programming Do Manifold Learning Too?." Proceedings of the European Conference on Genetic Programming (EuroGP), 2019. Best paper.
Published in Journal of the Royal Society of New Zealand, 2019
Recommended citation: Harith Al-Sahaf, Ying Bi, Qi Chen, Andrew Lensen, Yi Mei, Yanan Sun, Binh Tran, Bing Xue, Mengjie Zhang, "A survey on evolutionary machine learning." Journal of the Royal Society of New Zealand, 2019.
Published in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2018
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Automatically Evolving Difficult Benchmark Feature Selection Datasets with Genetic Programming." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2018.
Published in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2018
Recommended citation: Damien O'Neill, Andrew Lensen, Bing Xue, Mengjie Zhang, "Particle Swarm Optimisation for Feature Selection and Weighting in High-Dimensional Clustering." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2018.
Published in Proceedings of the European Conference on Genetic Programming (EuroGP), 2018
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Generating Redundant Features with Unsupervised Multi-tree Genetic Programming." Proceedings of the European Conference on Genetic Programming (EuroGP), 2018.
Published in Proceedings of the 11th International Conference on Simulated Evolution and Learning (SEAL), 2017
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "New Representations in Genetic Programming for Feature Construction in k-Means Clustering." Proceedings of the 11th International Conference on Simulated Evolution and Learning (SEAL), 2017.
Published in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2017
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "GPGC: genetic programming for automatic clustering using a flexible non-hyper-spherical graph-based approach." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2017.
Published in Proceedings of the European Conference on the Applications of Evolutionary Computation (EvoApplications), Part I, 2017
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Using Particle Swarm Optimisation and the Silhouette Metric to Estimate the Number of Clusters, Select Features, and Perform Clustering." Proceedings of the European Conference on the Applications of Evolutionary Computation (EvoApplications), Part I, 2017.
Published in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2017
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Improving k-means clustering with genetic programming for feature construction." Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion, 2017.
Published in Proceedings of the Symposium Series on Computational Intelligence (SSCI), 2016
Recommended citation: Andrew Lensen, Bing Xue, Mengjie Zhang, "Particle Swarm Optimisation Representations for Simultaneous Clustering and Feature Selection." Proceedings of the Symposium Series on Computational Intelligence (SSCI), 2016.
Published in Proceedings of the European Conference on Genetic Programming (EuroGP), 2016
Recommended citation: Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, Bing Xue, "Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data." Proceedings of the European Conference on Genetic Programming (EuroGP), 2016.
Published in Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ), 2015
Recommended citation: Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, Bing Xue, "A hybrid Genetic Programming approach to feature detection and image classification." Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ), 2015.
Published in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2015
Recommended citation: Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, Brijesh Verma, "Genetic Programming for algae detection in river images." Proceedings of the IEEE Congress on Evolutionary Computation (CEC), 2015.