Search
Search Results
-
Co-evolutionary Diversity Optimisation for the Traveling Thief Problem
Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given...
-
Learn to Fuse Input Features for Large-Deformation Registration with Differentiable Convex-Discrete Optimisation
Hybrid methods that combine learning-based features with conventional optimisation have become popular for medical image registration. The ConvexAdam...
-
Computing High-Quality Solutions for the Patient Admission Scheduling Problem Using Evolutionary Diversity Optimisation
Diversification in a set of solutions has become a hot research topic in the evolutionary computation community. It has been proven beneficial for...
-
A hybrid extreme learning machine model with harris hawks optimisation algorithm: an optimised model for product demand forecasting applications
Accurate and real-time product demand forecasting is the need of the hour in the world of supply chain management. Predicting future product demand...
-
Visualisation for Decision Support in Many-Objective Optimisation: State-of-the-art, Guidance and Future Directions
This chapter describes the state-of-the-art in visualisation for decision support processes in problems with many objectives. Visualisation is an...
-
Self Hyper-parameter Tuning for Stream Classification Algorithms
The new 5G mobile communication system era brings a new set of communication devices that will appear on the market. These devices will generate data...
-
Proximal Policy Optimisation for a Private Equity Recommitment System
Recommitments are essential for limited partner investors to maintain a target exposure to private equity. However, recommitting to new funds is...
-
Bridging Formal Methods and Machine Learning with Global Optimisation
Formal methods and machine learning are two research fields with drastically different foundations and philosophies. Formal methods utilise...
-
Multi-objective mixture design and optimisation of steel fiber reinforced UHPC using machine learning algorithms and metaheuristics
Ultra-high-performance concrete (UHPC) is a recent class of concrete with improved durability, rheological and mechanical and durability properties...
-
KNN-Averaging for Noisy Multi-objective Optimisation
Multi-objective optimisation is a popular approach for finding solutions to complex problems with large search spaces that reliably yields good...
-
Grid Search Optimization of Novel SNN-ESN Classifier on a Supercomputer Platform
This work is demonstrating the use of a supercomputer platform to optimise hyper-parameters of a proposed by the team novel SNN-ESN computational...
-
Trends in Data Stream Mining
Learning from data streams is a hot topic in machine learning and data mining. This article presents our recent work on the topic of learning from...
-
A Bayesian Optimisation Approach for Multidimensional Knapsack Problem
This paper considers the application of Bayesian optimisation to the well-known multidimensional knapsack problem which is strongly NP-hard. For the...
-
Handling Polynomial and Transcendental Functions in SMT via Unconstrained Optimisation and Topological Degree Test
We present a method for determining the satisfiability of quantifier-free first-order formulas modulo the theory of non-linear arithmetic over the...
-
Evolutionary Algorithms for Fair Machine Learning
At present, supervised machine learning algorithms are ubiquitously used to learn predictive models that have a major impact on people’s lives....
-
A Novel Grey Wolf Optimisation based CNN Classifier for Hyperspectral Image classification
Hyperspectral image (HI) analysis is becoming popular in remote sensing applications due to its high spectral resolution along with high spatial...
-
An evolving ensemble model of multi-stream convolutional neural networks for human action recognition in still images
Still image human action recognition (HAR) is a challenging problem owing to limited sources of information and large intra-class and small...
-
Revisiting Iterative Highly Efficient Optimisation Schemes in Medical Image Registration
3D registration remains one of the big challenges in medical imaging, especially when dealing with highly deformed anatomical structures such as...
-
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
In cardiac magnetic resonance (CMR) imaging, a 3D high-resolution segmentation of the heart is essential for detailed description of its anatomical...
-
Composite Surrogate for Likelihood-Free Bayesian Optimisation in High-Dimensional Settings of Activity-Based Transportation Models
Activity-based transportation models simulate demand and supply as a complex system and therefore large set of parameters need to be adjusted. One...