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08/18/2023
Improving Buoy Detection with Deep Transfer Learning for Mussel Farm Automation
The aquaculture sector in New Zealand is experiencing rapid expansion, w...
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04/18/2023
Differentiable Genetic Programming for High-dimensional Symbolic Regression
Symbolic regression (SR) is the process of discovering hidden relationsh...
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01/30/2023
Online Loss Function Learning
Loss function learning is a new meta-learning paradigm that aims to auto...
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12/07/2022
An Efficient Evolutionary Deep Learning Framework Based on Multi-source Transfer Learning to Evolve Deep Convolutional Neural Networks
Convolutional neural networks (CNNs) have constantly achieved better per...
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11/28/2022
Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations
Deep convolutional neural networks have proven their effectiveness, and ...
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09/19/2022
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning
In this paper, we develop upon the emerging topic of loss function learn...
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08/23/2022
Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues
Over recent years, there has been a rapid development of deep learning (...
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07/03/2022
Architecture Augmentation for Performance Predictor Based on Graph Isomorphism
Neural Architecture Search (NAS) can automatically design architectures ...
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04/13/2022
Deep Learning Model with GA based Feature Selection and Context Integration
Deep learning models have been very successful in computer vision and im...
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08/23/2021
Genetic Programming for Manifold Learning: Preserving Local Topology
Manifold learning methods are an invaluable tool in today's world of inc...
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08/09/2021
BenchENAS: A Benchmarking Platform for Evolutionary Neural Architecture Search
Neural architecture search (NAS), which automatically designs the archit...
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12/17/2020
Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning
Using evolutionary computation algorithms to solve multiple tasks with k...
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08/25/2020
A Survey on Evolutionary Neural Architecture Search
Deep Neural Networks (DNNs) have achieved great success in many applicat...
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08/15/2020
Evolving Deep Convolutional Neural Networks for Hyperspectral Image Denoising
Hyperspectral images (HSIs) are susceptible to various noise factors lea...
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07/03/2020
Surrogate-assisted Particle Swarm Optimisation for Evolving Variable-length Transferable Blocks for Image Classification
Deep convolutional neural networks have demonstrated promising performan...
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06/02/2020
A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems
Learning classifier systems (LCSs) originated from cognitive-science res...
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05/08/2020
Relatedness Measures to Aid the Transfer of Building Blocks among Multiple Tasks
Multitask Learning is a learning paradigm that deals with multiple diffe...
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04/23/2020
Constructing Complexity-efficient Features in XCS with Tree-based Rule Conditions
A major goal of machine learning is to create techniques that abstract a...
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01/28/2020
An Adaptive and Near Parameter-free Evolutionary Computation Approach Towards True Automation in AutoML
A common claim of evolutionary computation methods is that they can achi...
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01/27/2020
Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation
Data visualisation is a key tool in data mining for understanding big da...
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01/23/2020
Improving generalisation of AutoML systems with dynamic fitness evaluations
A common problem machine learning developers are faced with is overfitti...
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01/05/2020
Multi-Objective Genetic Programming for Manifold Learning: Balancing Quality and Dimensionality
Manifold learning techniques have become increasingly valuable as data c...
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11/20/2019
Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems
Due to its direct relevance to post-disaster operations, meter reading a...
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10/22/2019
Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis
Clustering is a difficult and widely-studied data mining task, with many...
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09/28/2019
Genetic Programming and Gradient Descent: A Memetic Approach to Binary Image Classification
Image classification is an essential task in computer vision, which aims...
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08/12/2019
Improving the Results of De novo Peptide Identification via Tandem Mass Spectrometry Using a Genetic Programming-based Scoring Function for Re-ranking Peptide-Spectrum Matches
De novo peptide sequencing algorithms have been widely used in proteomic...
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07/29/2019
Particle Swarm Optimisation for Evolving Deep Neural Networks for Image Classification by Evolving and Stacking Transferable Blocks
Deep Convolutional Neural Networks (CNNs) have been widely used in image...
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03/21/2019
Evolving Deep Neural Networks by Multi-objective Particle Swarm Optimization for Image Classification
In recent years, convolutional neural networks (CNNs) have become deeper...
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03/10/2019
A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks
Image classification is a difficult machine learning task, where Convolu...
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02/08/2019
Can Genetic Programming Do Manifold Learning Too?
Exploratory data analysis is a fundamental aspect of knowledge discovery...
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02/03/2019
GA-Novo: De Novo Peptide Sequencing via Tandem Mass Spectrometry using Genetic Algorithm
Proteomics is the large-scale analysis of the proteins. The common metho...
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10/28/2018
Automatically Evolving CNN Architectures Based on Blocks
The performance of Convolutional Neural Networks (CNNs) highly relies on...
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09/02/2018
Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization
Recently deep reinforcement learning (DRL) has achieved outstanding succ...
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08/20/2018
A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification
Convolutional Neural Networks (CNNs) have demonstrated their superiority...
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08/20/2018
A Hybrid DE Approach to Designing CNN for Image Classification
Convolutional Neural Networks (CNNs) have demonstrated their superiority...
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08/11/2018
Automatically Designing CNN Architectures Using Genetic Algorithm for Image Classification
Convolutional Neural Networks (CNNs) have gained a remarkable success on...
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04/17/2018
An Adaptive Clipping Approach for Proximal Policy Optimization
Very recently proximal policy optimization (PPO) algorithms have been pr...
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03/17/2018
Evolving Deep Convolutional Neural Networks by Variable-length Particle Swarm Optimization for Image Classification
Convolutional neural networks (CNNs) are one of the most effective deep ...
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02/02/2018
Generating Redundant Features with Unsupervised Multi-Tree Genetic Programming
Recently, feature selection has become an increasingly important area of...
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12/13/2017
A Particle Swarm Optimization-based Flexible Convolutional Auto-Encoder for Image Classification
Convolutional auto-encoders have shown their remarkable performance in s...
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10/30/2017
Evolving Deep Convolutional Neural Networks for Image Classification
Evolutionary computation methods have been successfully applied to neura...
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07/12/2016
Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation
In this paper, we propose a novel unsupervised domain adaptation algorit...
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10/15/2015
Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization
This paper addresses classification tasks on a particular target domain ...
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08/31/2015
Domain Generalization for Object Recognition with Multi-task Autoencoders
The problem of domain generalization is to take knowledge acquired from ...
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09/21/2014