55 citations · 141 across the 9 of their papers we have counts for
9 papers
Differentiable Genetic Programming for High-dimensional Symbolic Regression
Peng Zeng, Xiaotian Song, Andrew Lensen +4
Symbolic regression (SR) is the process of discovering hidden relationships from data with mathematical expressions, which is considered an effective way to reach interpretable mac…
Feature-based Image Matching for Identifying Individual Kākā
Fintan O'Sullivan, Kirita-Rose Escott, Rachael C. Shaw +1
This report investigates an unsupervised, feature-based image matching pipeline for the novel application of identifying individual kākā. Applied with a similarity network for clus…
Genetic Programming for Manifold Learning: Preserving Local Topology
Andrew Lensen, Bing Xue, Mengjie Zhang
Manifold learning methods are an invaluable tool in today's world of increasingly huge datasets. Manifold learning algorithms can discover a much lower-dimensional representation (…
Mining Feature Relationships in Data
Andrew Lensen
When faced with a new dataset, most practitioners begin by performing exploratory data analysis to discover interesting patterns and characteristics within data. Techniques such as…
Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation
Andrew Lensen, Bing Xue, Mengjie Zhang
Data visualisation is a key tool in data mining for understanding big datasets. Many visualisation methods have been proposed, including the well-regarded state-of-the-art method t…
Multi-Objective Genetic Programming for Manifold Learning: Balancing Quality and Dimensionality
Andrew Lensen, Mengjie Zhang, Bing Xue
Manifold learning techniques have become increasingly valuable as data continues to grow in size. By discovering a lower-dimensional representation (embedding) of the structure of…
Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis
Andrew Lensen, Bing Xue, Mengjie Zhang
Clustering is a difficult and widely-studied data mining task, with many varieties of clustering algorithms proposed in the literature. Nearly all algorithms use a similarity measu…
Can Genetic Programming Do Manifold Learning Too?
Andrew Lensen, Bing Xue, Mengjie Zhang
Exploratory data analysis is a fundamental aspect of knowledge discovery that aims to find the main characteristics of a dataset. Dimensionality reduction, such as manifold learnin…
Generating Redundant Features with Unsupervised Multi-Tree Genetic Programming
Andrew Lensen, Bing Xue, Mengjie Zhang
Recently, feature selection has become an increasingly important area of research due to the surge in high-dimensional datasets in all areas of modern life. A plethora of feature s…