School of Engineering and Computer Science Te Kura Mātai Pūkaha, Pūrorohiko

Feature Analysis, Selection, and Learning in Image and Pattern Recognition (FASLIP)

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[02 May 2024] 3-Mins Presentation: Shanshan, Yida, Hengzhe, Chunyu, Carl, Rimas, Nan, Fei, Qinyu, Yun

[18 April 2024] Yuye Zhang: Multimodal data analysis

[11 April 2024] Prof. Xin Yao's talk on What Can Evolutionary Computation Do For You

[04 April 2024] Binke Xu: Ensemble Learning based on Neural Networks for Tree Image Segmentation

[28 March 2024] Taran John: Evolving Feature Extraction Models for Melanoma Detection: A Co-operative Co-evolution Approach

[21 March 2024] Qinyu Wang: Genetic Programming with Aggregate Channel Features for Flower Localization Using Limited Training Data

[14 March 2024] Serafina Slevin: Machine Learning for Ice Melting Data Analysis

[29 February 2024] Junjia Feng: Multimodal Aspect-Oriented Sentiment Classification

[22 February 2024] Mingqian Lin: application of differentiable architecture search in image classification

[15 February 2024] Carl McMillan: Evolutionary Deep Learning for Building a Buoyancy Alerting System in NZ Mussel Farms

[8 February 2024] Mohamad Rimas Mohamad Anfar: Genetic Programming for Interpretable Symbolic Regression

[1 February 2024] Hengzhe Zhang: Improving Generalization of Evolutionary Feature Construction with Minimal Complexity Knee Points in Regression

[18 January 2024] Prof. Dr. Frank-Peter Schilling, Zurich University of Applied Sciences, Research at ZHAW’s Centre for AI & Mitigation of Motion Artifacts in Cone-beam CT with Deep Learning

[11 January 2024] Chunyu Wang: proposal rehearsal: Genetic Programming for Multi-output Symbolic Regression

[14 December 2023] Qinyu Wang: Genetic Programming with Aggregate Channel Features for Flower Localization

[07 December 2023] Xinming Shi: Evolving circuits using genetic programming

[30 November 2023] Emrah Hancer: Nuclei Segmentation and Mitosis Detection with Deep Learning

[23 November 2023] Talk 2: Hamish Oliver Greig O'Keeffe: Real-Time Instance Segmentation Techniques using Neural Networks for the Assessment of Green-Lipped Mussels (IVCNZ2023)

[23 November 2023] Talk1: Mohamad Rimas Mohamad Anfar: Bloating Reduction in Symbolic Regression through Function Frequency-based Tree Substitution in Genetic Programming (AJICAI2023)

[16 November 2023] Taran John: PhD proposal seminar rehearsal: Utilising Machine Learning Techniques to Extract Clinically Oriented Features for Skin Cancer Detection

[09 November 2023] Chunyu Wang: PhD proposal seminar rehearsal: Genetic Programming for Multi-output Symbolic Regression

[02 November 2023] Dylon Zeng: A New Genetic Programming-Based Approach to Object Detection in Mussel Farm Images

[26 October 2023] Ziyi Sun: An Improved Mask R-CNN for Instance Segmentation of Tree Crowns in Aerial Imagery

[19 October 2023] Carl McMillan: Improving Buoy Detection with Deep Transfer Learning for Mussel Farm Automation Computation

[12 October 2023] Lin Dong: Image features and image operators

[05 October 2023] Binke Xu: Ensemble learning for tree image segmentation

[28 September 2023] Peng Wang: M3GP

[21 September 2023] Junhao Huang: Automated Design of Efficient Multi-Scale Networks via Multi-Path Weight Sampling

[14 September 2023] Yun Zhou: Data preprocessing and machine learning for analyzing the blend data of the Hoki and Mackerel fish

[07 September 2023] Huixiang Zhen: Model Selection based Offline Data-driven Evolutionary Algorithm

[31 August 2023] Huixiang Zhen: MSEA: A New Model Selection based Offline Data-driven Evolutionary Algorithm

[24 August 2023] IEEE symposium presentation practice: Chunyu Wang, Carl McMillan, Mohamad Rimas Mohamad Anfar, and Binke Xue

[17 August 2023] Xie Cheng: A Model Compression Method Applied to the Model of Turntable Servo System

[10 August 2023] Hengzhe Zhang: Evolutionary feature construction for symbolic regression

[03 August 2023] Botao Jiao: Semi-Supervised Unbiased Hoeffding Trees for Imbalanced Data Stream Classification

[28 July 2023] Carl McMillan: Mussel farm buoy detection

[21 July 2023] Shanshan Tang: Multi-task learning with individual feature-based task correlation matrices for Alzheimer's disease prediction

[13 July 2023] Mohamad Rimas Mohamad Anfar: Bloat Control for GP for Symbolic Regression

[06 July 2023] Kaan Demir: Co-operative Co-evolutionary Many-objective Embedded Multi-label Feature Selection with Decomposition-based PSO

[29 June 2023] Hengzhe Zhang: "Genetic Programming-based Evolutionary Feature Construction for Heterogeneous Ensemble Learning" and "Bike Lane Usage Forecasting Using Evolutionary Feature Construction"

[22 June 2023] Hengzhe Zhang: A Double Lexicase Selection Operator for Bloat Control in Evolutionary Feature Construction for Regression

[15 June 2023] Sara: Duck Classification

[08 June 2023] Christian Raymond: Fast and Efficient Local-Search for Genetic Programming Based Loss Function Learning

[01 June 2023] Shihui Liu: Hyperspectral Real-time Processing Technology

[25 May 2023] Cheng Xie: A Particle Swarm Optimization(PSO)-based Reversible Residual Neural Network Architecture Search(NAS)

[18 May 2023] Zhixing Huang: Introduction on GP to DJSS

[11 May 2023] Huixiang Zhen: Neural Architecture Transfer

[04 May 2023] Gonglin Yuan: An Effective One-shot Neural Architecture Search Method with Supernet Fine-Tuning for Image Classification

[27 April 2023] Jiabin Lin: Evolutionary multi-task learning based on knowledge sharing for feature selection in classification

[20 April 2023] GECCO tutorial on Lexicase Selection-2

[13 April 2023] GECCO tutorial on Lexicase Selection-1

[06 April 2023] Jesse Wood: LaTex is all you need

[30 March 2023] Binke Xu: Wellington tree image analysis

[23 March 2023] Junhao Huang: Multi-Objective Evolutionary Search of Compact Convolutional Neural Networks with Training-Free Estimation

[16 March 2023] Anton Lee: Balancing the Stability-Plasticity Dilemma with Online Stability Tuning for Continual Learning

[09 March 2023] Alessandro Pol: Shellfish Mood in Aquaculture

[02 March 2023] Chunyu Wang: Permutation based Feature Selection in Genetic Programming for Symbolic Regression and Shapley value

[23 February 2023] Yuwei Sun: Meta Learning in Decentralized Neural Networks through the lens of Global Workspace Theory Slides

[16 February 2023] YiBin Sun: SOKNL-Integrating KNN with Adaptive Random Forest for Data Stream Regression

[09 February 2023] Zhenshou Song: Online Data-Driven Optimization for Many Objective Optimization Problems

[02 February 2023] Hengzhe Zhang: GP-based Ensemble Learning: Tips and Tricks

[26 January 2023] Huixiang Zhen: Data-driven evolutionary algorithms and evolutionary sampling agent

[19 January 2023] Botao Jiao: Semi-supervised Active Learning for Data Stream with Concept Drift

[12 January 2023] Shanshan Tang: Research on Multi-Task Learning Algorithms for Alzheimer's Disease Prediction

[15 December 2022] Qinyu Wang: PhD proposal seminar---Genetic Programming for Fine-Grained Image Classification

[08 December 2022] Zhixing Huang: A Further Investigation to Improve Linear Genetic Programming in Dynamic Job Shop Scheduling

[01 December 2022] Binh Dang: Operation-based Greedy Algorithm for Discounted Knapsack Problem and Jesse Wood: Automated Fish Classification Slides

[17 November 2022] Person: Michael: How long is the fish? Qinglan Fan: Evolving effective ensembles for image classification using multi-objective multi-tree genetic programming and Ruwang Jiao: Handling different preferences between objectives for multi-objective feature feature in classification

[10 November 2022] Prof. Xin Yao's talk on What Can Evolutionary Computation Do For You

[03 November 2022] Hengzhe Zhang: GP and semantic GP-2

[13 October 2022] Hengzhe Zhang: GP and semantic GP-1

[06 October 2022] Ziyi Sun: Mask RCNN

[29 September 2022] Qinyu Wang: GP for image classification, research proposal rehearsal

[22 September 2022] Person: Dr Faizal Hafiz from Université Côte d'Azur, France, "Data Driven Modeling, Fundamental Challenges & Some Proposed Solutions" Abstract

[15 September 2022] 6th Anniversary Day celebration

[08 September 2022] Person: Prof. Jinyan Li from University of Technology Sydney, "Some optimization and machine learning problems in bioinformatics"

[01 September 2022] Dylon Zeng: Multi-Object Tracking for Mussel Farms: A Non-Neural Network Approach

[25 August 2022] Jesse Wood: Automated Fish Classification

[18 August 2022] Kaan Demir: Feature Selection for Multi-label Classification

[11 August 2022] Hayden Andersen: explainable/interpretable AI

[04 August 2022] Qinglan Fan: Genetic Programming for Image Classification: A New Program Representation with Flexible Feature Reuse

[28 July 2022] Interviews from Sentient Lab/Sentient Technologies-2 chaired by Qi Chen

[23 June 2022] Phil Waknell's talk on The 3 Magic Ingredients of Amazing Presentations, and David JP Philips's talk on The magical science of storytellingrecommended/chaired by Jiabin Lin

[14 April 2022] Christian Raymond: Multi-objective GP with AWS for Symbolic Regression

[17 February 2022] Hayden Andersen: PhD proposal seminar rehearsal on Evolving Human-Friendly Explanations

[10 February 2022] Kaan Demir: PhD proposal seminar rehearsal on Sparsity-based Feature Selection for Multi-label Classification

[03 February 2022] Qi Chen : Semantic Genetic Programming

[20 Jan 2022] Bach Nguyen : Simultaneous features and instance selection

[13 Jan 2022] Qurrat Ul Ain : GP for skin cancer image classification

[25 June 2020] Qi Chen: MIC for feature selection in Symbolic Regression

[16 Dec 2021] FASLIP Group Catch up, Free Discussions

[09 Dec 2021] Christian Raymond PhD proposal rehearsal seminar Meta Learning for Loss Function Learning

[02 Dec 2021] Wenbin Pei: Genetic Programming for Unbalanced Classification

[11 June 2020] Bo Peng : Feature Extraction and Construction Using Genetic Programming for Rotating Machinery Fault Diagnosis

[4 June 2020] Damien O'Neil: Neural Architecture Search for Sparse DenseNets with Dynamic Compression

[28 May 2020] Qinglan Fan: A Region Adaptive Image Classification Approach Using Genetic Programming

[21 May 2020] Ying Bi: Genetic Programming for Feature Learning in Image Classification

[14 May 2020] Ying Bi: Genetic Programming for Feature Learning in Image Classification

[07 May 2020] Qurrat Ul Ain: A Genetic Programming Approach to Feature Construction for Ensemble Learning in Skin Cancer Detection

[30 April 2020] Hang Xue: Segmented Initialization and Offspring Modification in Evolutionary Algorithms for Bi-objective Feature Selection

[23 April 2020] Baligh Al-Helali: Genetic programming for symbolic regression with missing data: feature selection, transfer learning

[16 April 2020] Bach Hoai Nguyen: Multi-Objective Optimisation II: NSGAII, SPEA2 and MOEA/D

[09 April 2020] Bach Hoai Nguyen: Multi-Objective Optimisation I: basics and NSGAII

[02 April 2020] Samantha Azari Experience Sharing for PhD thesis and oral defence.

[25 March 2020] Wenbin Pei genetic programming for imbalanced classification using cost-sensitive learning

[19 March 2020] Wenbin Pei genetic programming for imbalanced classification using cost-sensitive learning

[05 March 2020] Peng Wang multimodal EC algorithms for feature selection and machine learning

[27 Feb 2020] Ramya Anasseriyil Viswambaran: genetic algorithms to evolve RNN

[20 Feb 2020] Ramya Anasseriyil Viswambaran: Introduction to RNN

[14 Feb 2020] Ke Chen: Hybrid PSO and DE for for feature selection

[07 Feb 2020] Ideas and Discussions on Paper Writing

[31 Jan 2020] Ideas and Discussions on Paper Writing

[15 Jan 2020] Ying Bi's GECCO idea: MOGP for feature learning in face image classification
[15 Jan 2020] Andrew Lensen: GP for manifold learning

[19 Dec 2019] Ben Evans: Improving generalisation of AutoML systems with dynamic fitness evaluations

[12 Dec 2019] Hang Xu: multi-objective feature selection with analysis on duplicated solutions

[05 Dec 2019] Kosisochukwu Madukwe: Text Mining

[28 Nov 2019] Xiaoying Gao: Text Mining

[21 Nov 2019] Baolei Li: decomposition based evolutionary multi-objective optimisation

[14 Nov 2019] Andrew Lensen: GP for Manifold Learning

[07 Nov 2019] Andrew Lensen: GP for Manifold Learning

[31 Oct 2019] Fangfang Zhang: GP for flexible dynamic job shop scheduling

[24 Oct 2019] Ying Bi: Feature learning for image classification

[17 Oct 2019] Ying Bi: GP with image descriptor for feature learning to image classification

[10 Oct 2019] Wenbin Pei: cost-sensitive learning for high-dimensional imbalanced data classification

[03 Oct 2019] Bin Wang: Bin's PhD proposal rehearsal --- Evolving Neural Networks

[26 Sep 2019] Qurrat Ul Ain: multi-tree GP for skin cancer image classification

[19 Sep 2019] Baligh Al-Helali: Genetic Programming for symbolic regression

[12 Sep 2019] Bach Hoai Nguyen: multi-objective feature selection with dynamic decomposition based multi-objective algorithms

[05 Sep 2019] Ke Chen: Multi-tasking and feature selection

[29 Aug 2019] Jiabin Lin: An introduction to Multi-tasking

[22 Aug 2019] Ke Chen: feature selection based multi-tasking optimisation

[15 Aug 2019] Qi Chen: Transfer learning in GP for symbolic regression

[08 Aug 2019] Hang Xue: Evolutionary Multi-objective Optimisation

[01 Aug 2019] Hang Xue: Evolutionary Multi-objective Optimisation

[25 Jul 2019] Damien O'Neil: Evolution of Adjacency Matrices for Sparsity of Connection in DenseNets

[18 Jul 2019] Miao Lu: Satellite Images Analysis

[04 Jul 2019] Bach Hoai Nguyen: Population-based Ensemble Classifier Induction for Domain Adaptation

[27 Jun 2019] Ying Bi: An Automated Ensemble Learning Framework Using Genetic Programming for Image Classification

[20 Jun 2019] Everyone: what learnt from CEC 2019

[06 Jun 2019] Ramya Anasseriyil Viswambaran: PhD proposal rehearsal on Evolving Recurrent Neural Networks

[30 May 2019]Baligh Al-Helali: Interval Function based GP for Symbolic Regression on Incomplete Data

[23 May 2019] Wenbin Pei: Cost Sensitive Learning

[17 May 2019] Su Nguyen: GP and visualisation

[09 May 2019] Ramya Anasseriyil Viswambaran: PhD proposal rehearsal on Evolving Recurrent Neural Networks

[02 May 2019] Bin Wang: Evolving Deep Neural Networks 3

[18 April 2019] Bin Wang: Evolving Deep Neural Networks 2

[11 April 2019] Bin Wang: Evolving Deep Neural Networks 1

[04 April 2019] Ke Chen: Multi-modal Optimisation using PSO

[28 Mar 2019] Jiabin Lin: Evolutionary Multi-tasking Optimisation

[21 Mar 2019] Beolei Li: EC for multi-modal optimisation

[14 Mar 2019] Yanan Sun: Evolving Deep NNs and Many-objective Optimisation

[07 Mar 2019] Yanan Sun: Evolving Deep NNs and Many-objective Optimisation

[28 Feb 2019] Damien O'Neil: PhD proposal rehearsal

[21 Feb 2019] Ben Evan's Research on Ensemble Learning, AutoML and Explainable ML 2

[14 Feb 2019] Ben Evan's Research on Ensemble Learning, AutoML and Explainable ML 1

[24 Jan 2019] Everyone: CEC and GECCO papers

[10 Jan 2019] Everyone: CEC and GECCO papers

[19 Dec 2018] Damien O'Neil: PhD Research Objectives

[12 Dec 2018] Ke Chen: AI presentation rehearsal

[28 Nov 2018] Damien O'Neil: IEEE AGM speech, and Madhi’s proposal seminar rehearsal

[21 Nov 2018] Qurrat Ul Ain: A Multi-tree Genetic Programming Representation for Melanoma Detection Using Local and Global Features

[14 Nov 2018] Shima Afzali: Foreground and Background Feature Fusion using a Convex Hull based Center Prior for Salient Object Detection

[01 Nov 2018] Wenbin Pei: PhD Proposal seminar rehearsal

[25 Oct 2018] Wenbin Pei: PhD Proposal seminar rehearsal

[18 Oct 2018] Ying Bi: Deep Random Forest

[11 Oct 2018] Wenbin Pei: New Fitness Functions in Genetic Programming for Classification with High-dimensional Unbalanced Data

[04 Oct 2018] Baligh Al-Helali: A Hybrid GP-KNN Imputation for Symbolic Regression with Missing Values

[27 Sep 2018] Fangfang Zhang: Introduction to Job Shop scheduling

[20 Sep 2018] Fangfang Zhang: Introduction to Job Shop scheduling

[13 Sep 2018]Baligh Al-Helali: Proposed Research Objectives in PhD

[06 Sep 2018] Wenbin Pei: Proposed Research Objectives

[30 Aug 2018] [78] Checklist for making a presentation

[23 Aug 2018] [77] Checklist for making a presentation --- slides

[16 Aug 2018] [76] Checklist for writing a paper

[09 Aug 2018] [75] Checklist for writing a paper

[02 Aug 2018] [74] Cao Truong Tran: EC for Missing Data in Classification

[26 July 2018] [73] Yanan Sun Using PSO/GA to evolve Deep CNNs

[19 July 2018] [72] Baligh Al-Helali: Using Symbolic Regression to Handle Missing Data in Symbolic Regression

[12 July 2018] [71] Binh Tran Variable length PSO for Feature Selection

[05 July 2018] [70] Hoai Bach Nguyen: Problems with Binary PSO and Sticky Binary PSO

[28 June 2018] Damien O'Neill: Co-evolution with GP to evolve ANNs

[21 June 2018] Qi Chen: Transfer Learning in GP for symbolic regression

[14 June 2018] Wenbin Pei: Layered GP for Classification

[31 May 2018] Wenbin Pei: Layered GP for Classification

[31 May 2018] Discussions on Feature Fusion and Convex-Hull-based Center Prior for Salient Object Detection by Shima Afzali

[24 May 2018] Samantha Azari Genetic Programming for Preprocessing Tandem Mass Spectra to Improve the Reliability of Peptide Identification

[17 May 2018] Samantha Azari Genetic Programming for Preprocessing Tandem Mass Spectra to Improve the Reliability of Peptide Identification

[10 May 2018] Prof. Juergen Branke about Learning to optimise – optimal learning

[03 May 2018] Discussions on Feature Fusion and Convex-Hull-based Center Prior for Salient Object Detection by Shima Afzali

[26 April 2018] Discussions on Introduction to Salient Object Detection by Shima Afzali

[19 April 2018] Discussions on Genetic Programming for Evolutionary Deep Learning for Image Classification by Ben Evans

[12 April 2018] Discussions on Rough Set by Wenbin Pei

[05 April 2018] Discussions on Rough Set by Wenbin Pei

[29 March 2018] Discussions on image classification by Ying Bi

[22 March 2018] Discussions on PSO for Simultaneous Feature Selection and Weighting in High-Dimensional Clustering by Damien O'Neill

[9 March 2018] Discussions on transfer learning

[1 March 2018] Discussions on transfer learning

[22 Feb 2018] Discussions of our SUPER BUSY time in the past weeks, and ~two minutes to introduce our CEC and GECCO papers
  • Discussions of our SUPER BUSY time in the past weeks
  • Samaneh Azari CEC 2018 paper: Genetic Programming for Preprocessing Tandem Mass Spectra to Improve the Reliability of Peptide Identification

[15 Feb 2018] Prof. Zhihua Zhou's visit and gives a talk.

[8 Feb 2018] We are having a break after writing CEC and GECCO papers

[1 Feb 2018] We are submitting CEC and writing GECCO papers! smile

[25 Jan 2018] EC for missing data in classification by Cao Truong Tran

[18 Jan 2018] My research on EC for missing data in classification by Cao Truong Tran

Thanks Truong again for his great lecture on missing data. Some pictures pictures (Picture 1, Picture 2 , Picture 3 ) remind what he has discussed with us, and how to use regression to do imputation.

Another very important message is how he got ideas from different areas to come up with excellent research, forming his big PhD thesis.

[11 Jan 2018] Class Dependent Multiple Feature Construction Using Genetic Programming for High-Dimensional Data by Binh Tran

[21 Dec] FASLIP End of the Year Celebration smile

[14 Dec 2017] A New Representation in PSO for Discretisation-Based Feature Selection by Binh Tran

[07 Dec 2017] Particle Swarm Optimisation for Feature Selection on High-dimensional Data: Local Search and Selection Bias by Binh Tran

[30 Nov 2017] Genetic Programming for Feature Construction and Selection in Classification on High-dimensional Data by Binh Tran

[12 Oct 2017, 19 Oct 2017, 26 Oct 2017, 2 Nov 2017, 16 Nov 2017] Why using EC in your Research by EVERYONE.

[12 Oct 2017] Pros and Cons of Different EC methods, and Why using EC in Your Research
  • Comparison among five evolutionary-based optimization algorithms Link: pdf here
  • Comparison between genetic algorithms and particle swarm optimization Link: pdf here
  • Comparison of Three Evolutionary Algorithms: GA, PSO, and DE Link

[05 Oct 2017] Why using EC in Your Research
  • Comparison among five evolutionary-based optimization algorithms Link: pdf here
  • Comparison between genetic algorithms and particle swarm optimization Link: pdf here
  • Comparison of Three Evolutionary Algorithms: GA, PSO, and DE Link

[28 Sep 2017] Discussions and Celebrations (photos coming soon)

[21 Sep 2017] What Can Evolutionary Computation Do For You? II

[14 Sep 2017] What Can Evolutionary Computation Do For You? I

What Can Evolutionary Computation Do For You: Slides here and Video here

Paper in Nature: From evolutionary computation to the evolution of things: Link here

[07 Sep 2017] Auto-encoder in Deep CNN by Dr Yanan Sun

Here is a very good tutorial for understanding auto-encoder:

http://deeplearning.stanford.edu/wiki/index.php/Autoencoders_and_Sparsity

[23 Aug 2017] Qurrat Ul Ain Proposal Seminar Rehearsal

Title: Feature Manipulation using Genetic Programming for Medical Image Classification

[09 Aug 2017] Deep CNN by Dr Yanan Sun

Here is a very good tutorial for understanding auto-encoder:

http://deeplearning.stanford.edu/wiki/index.php/Autoencoders_and_Sparsity

[27 Jul 2017] Plan for next six weeks and GECCO experiences

Everyone discuss their plan for the next six months, and others gave suggestions.

[11 Jul 2017] Self-adaptive Particle Swarm Optimization for Large-scale Feature Selection in Classification by Dr Yu Xue

This is Dr Yu Xue's recent paper, submitted to a journal. A popular paper on self-adaptive differential evolution is Self-adaptive differential evolution algorithm for numerical optimization

[06 Jul 2017] Self-adaptive Particle Swarm Optimization for Large-scale Feature Selection in Classification by Dr Yu Xue

This is Dr Yu Xue's recent paper, submitted to a journal. A popular paper on self-adaptive differential evolution is Self-adaptive differential evolution algorithm for numerical optimization

[29 Jun 2017] Geometric Semantic Operators in GP for Symbolic Regression by Qi Chen

Qi will discuss her recent work on Geometric Semantic Operators in GP for Symbolic Regression:

[22 Jun 2017] Samantha Azari Proposal Seminar Rehearsal

Her proposal title is Identification of Modified and Unmodified Peptides of Proteins Using Tandem Mass Spectra Data

[15 Jun 2017] GP for image classification by Dr Harith Al-Sahaf

[08 Jun 2017] GP for image analysis by Dr Harith Al-Sahaf

*Andrew's CEC 2015 paper: Genetic programming for algae detection in river images

[01 Jun 2017] GP for image analysis by Dr Harith Al-Sahaf

*CEC 2015 Best Award Paper: Image Descriptor: A Genetic Programming Approach to Multiclass Texture Classification

[25 May 2017] Edge detection using Genetic Programming by Ying Bi

Wenlong's paper in CEC 2014 Unsupervised learning for edge detection using Genetic Programming

[18 May 2017] Sentiment Analysis by Martin Mikula

Sentiment analysis: SApresentation.pptx

[11 May 2017] GP for classification

A Survey on the Application of Genetic Programming to Classification

[04 May 2017] Shima Afzali Proposal Seminar Rehearsal

Title: Salient Object Detection based on Input Feature Set Improvement

[27 April 2017] Basic Machine Learning Algorithms

[13 April 2017] Geometric semantic GP by Qi Chen

[06 April 2017] Geometric semantic GP by Qi Chen

[30 Mar 2017] Discussion on MOEA/D by Hoai Bach Nguyen

  • Hoai Bach's Slides here
  • Prof. Qingfu Zhang has a website for MOEA/D, where you can find the original paper and related study on MOEA/D: Link here

[23 Mar 2017] Samantha Azari Research Topics

[16 Mar 2017] Samantha Azari Research Topics

[01 Mar 2017] Introduction to EMO: SPEA2 by Prof Bing Xue

  • Introduction to Evolutionary Multi-objective Optimisation I [[http://ecs.victoria.ac.nz/foswiki/pub/Groups/ECRG/Talks/EMO.pdf][EMO.pdf];EMO_part2.pdf
  • Introduction to Evolutionary Multi-objective Optimisation II : EMONSGAII_and_SPEA2.pdf

[23 Feb 2017] Introduction to EMO: NSGAII by Prof Bing Xue

[16 Feb 2017] How to write a PhD proposal

[26 Jan 2017] Clustering using EC by Andrew Lensen

From Andrew: I will discuss some of the challenges faced in clustering (and particularly, why EC is useful for addressing them!). I am hoping the session will run more as an informal "tutorial"-type discussion on clustering, and so I won't ask that you read any recent papers in the area, especially what with the ongoing CEC and GECCO pressures. What would be very useful however, is if you could quickly review how k-means clustering works, and have a bit of a think about what limitations it has --- much of my research is based on limitations of k-means, and so understanding it well is important. In particular, if you haven't had a clustering lecture for a long time (or ever), please take 15 mins or so to read up. https://en.wikipedia.org/wiki/K-means_clustering actually has a very nice discussion on k-means with a lot of detail, though it can be a bit technical for a first look.

[19 Jan 2017] GP for multi-class classification by Dr Harith Al-Sahaf

From Harith: Utilising GP for multi class classification tasks has been broadly investigated and different methods have been proposed. It is no an easy job (in fact infeasible) to explore/discuss all those methods in a 50 minutes talk; therefore, I will try to, briefly, touch some of the basic methods/approaches. In order to save the trees and your time, my list of papers comprises only a single very good journal article, a bit old one though. Please do not spend too long time on the paper: A Survey on the Application of Genetic Programming to Classification

[22 Dec 2016] Discussions on transfer learning

I Attachment Action Size Date Who Comment
Feb23 - Yuwei Sun.pdfpdf Feb23 - Yuwei Sun.pdf manage 11 MB 24 Feb 2023 - 09:51 Main.fzhang  
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