Search Results for author: Shahryar Rahnamayan

Found 23 papers, 2 papers with code

Multi-objective Binary Coordinate Search for Feature Selection

no code implementations20 Feb 2024 Sevil Zanjani Miyandoab, Shahryar Rahnamayan, Azam Asilian Bidgoli

For this purpose, we have proposed the binary multi-objective coordinate search (MOCS) algorithm to solve large-scale feature selection problems.

feature selection

Compact NSGA-II for Multi-objective Feature Selection

no code implementations20 Feb 2024 Sevil Zanjani Miyandoab, Shahryar Rahnamayan, Azam Asilian Bidgoli

In this regard, we define feature selection as a multi-objective binary optimization task with the objectives of maximizing classification accuracy and minimizing the number of selected features.

Evolutionary Algorithms feature selection

Ranking Loss and Sequestering Learning for Reducing Image Search Bias in Histopathology

no code implementations15 Apr 2023 Pooria Mazaheri, Azam Asilian Bidgoli, Shahryar Rahnamayan, H. R. Tizhoosh

By forcing the model to learn the ranking of matched outputs, the representation learning is customized toward image search instead of learning a class label.

Image Retrieval Representation Learning +1

Variable Functioning and Its Application to Large Scale Steel Frame Design Optimization

no code implementations15 May 2022 Amir H Gandomi, Kalyanmoy Deb, Ronald C Averill, Shahryar Rahnamayan, Mohammad Nabi Omidvar

By using problem structure analysis technique and engineering expert knowledge, the $Fx$ method is used to enhance the steel frame design optimization process as a complex real-world problem.

Forming Local Intersections of Projections for Classifying and Searching Histopathology Images

no code implementations8 Aug 2020 Aditya Sriram, Shivam Kalra, Morteza Babaie, Brady Kieffer, Waddah Al Drobi, Shahryar Rahnamayan, Hany Kashani, Hamid. R. Tizhoosh

In this paper, we propose a novel image descriptor called Forming Local Intersections of Projections (FLIP) and its multi-resolution version (mFLIP) for representing histopathology images.

Image-Based Benchmarking and Visualization for Large-Scale Global Optimization

no code implementations24 Jul 2020 Kyle Robert Harrison, Azam Asilian Bidgoli, Shahryar Rahnamayan, Kalyanmoy Deb

In the context of optimization, visualization techniques can be useful for understanding the behaviour of optimization algorithms and can even provide a means to facilitate human interaction with an optimizer.

Benchmarking Dimensionality Reduction +1

Multi-objective Optimal Control of Dynamic Integrated Model of Climate and Economy: Evolution in Action

no code implementations29 Jun 2020 Mostapha Kalami Heris, Shahryar Rahnamayan

One of the widely used models for studying economics of climate change is the Dynamic Integrated model of Climate and Economy (DICE), which has been developed by Professor William Nordhaus, one of the laureates of the 2018 Nobel Memorial Prize in Economic Sciences.

Towards Solving Large-scale Expensive Optimization Problems Efficiently Using Coordinate Descent Algorithm

no code implementations7 Mar 2020 Shahryar Rahnamayan, Seyed Jalaleddin Mousavirad

To the best our knowledge, there is no significant study to assess benchmark functions with various dimensions and landscape properties to investigate CD algorithm.

Opposition based Ensemble Micro Differential Evolution

no code implementations8 Sep 2017 Hojjat Salehinejad, Shahryar Rahnamayan, Hamid. R. Tizhoosh

Differential evolution (DE) algorithm with a small population size is called Micro-DE (MDE).

Benchmarking

Learning Opposites Using Neural Networks

no code implementations16 Sep 2016 Shivam Kalra, Aditya Sriram, Shahryar Rahnamayan, H. R. Tizhoosh

In this paper, we introduce an approach to learn type-II opposites from the given inputs and their outputs using the artificial neural networks (ANNs).

Evolutionary Algorithms Vocal Bursts Type Prediction

Automated Resolution Selection for Image Segmentation

no code implementations22 May 2016 Fares Al-Qunaieer, Hamid. R. Tizhoosh, Shahryar Rahnamayan

This paper introduces a framework for the automated selection of the best resolution for image segmentation.

Image Segmentation Segmentation +1

Evolutionary Projection Selection for Radon Barcodes

no code implementations16 Apr 2016 Hamid. R. Tizhoosh, Shahryar Rahnamayan

A small number of equidistant projections, e. g., 4 or 8, is generally used to generate short barcodes.

Diversity Enhancement for Micro-Differential Evolution

no code implementations25 Dec 2015 Hojjat Salehinejad, Shahryar Rahnamayan, Hamid. R. Tizhoosh

Furthermore, comprehensive comparative simulations and analysis on performance of the MDE algorithms over various mutation schemes, population sizes, problem types (i. e. uni-modal, multi-modal, and composite), problem dimensionalities, and mutation factor ranges are conducted by considering population diversity analysis for stagnation and trapping in local optimum situations.

Learning Opposites with Evolving Rules

no code implementations21 Apr 2015 Hamid. R. Tizhoosh, Shahryar Rahnamayan

This, of course, is a very naive estimate of the actual or true (non-linear) opposite $\breve{x}_{II}$, which has been called type-II opposite in literature.

Evolutionary Algorithms

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