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From Genetic Variation to Probabilistic Modeling
Genetic algorithms ⦓GAs) [53, 83] are stochastic optimization methods inspired by natural evolution and genetics. Over the last few decades, GAs have...
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Hierarchical Bayesian Optimization Algorithm
The previous chapter has discussed how hierarchy can be used to reduce problem complexity in black-box optimization. Additionally, the chapter has...
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The Challenge of Hierarchical Difficulty
Thus far, we have examined the Bayesian optimization algorithm (BOA), empirical results of its application to several problems of bounded difficulty,...
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Hierarchical BOA in the Real World
The last chapter designed hBOA, which was shown to provide scalable solution for hierarchical traps. Since hierarchical traps were designed to test...
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Scalability Analysis
The empirical results of the last chapter were tantalizing. Easy and hard problems were automatically solved without user intervention in polynomial...
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Summary and Conclusions
The purpose of this chapter is to provide a summary of main contributions of this work and outline important conclusions.
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Bayesian Optimization Algorithm
The previous chapter argued that using probabilistic models with multivariate interactions is a powerful approach to solving problems of bounded...
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Probabilistic Model-Building Genetic Algorithms
The previous chapter showed that variation operators in genetic and evolutionary algorithms can be replaced by learning a probabilistic model of...
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Information flow control for comparative privacy analyses
The prevalence of web tracking and its key characteristics have been extensively investigated by the research community by means of large-scale web...
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A quantitative analysis of the security of PoW-based blockchains
This study analyzes the security implications of Proof-of-Work blockchains with respect to the stale block rate and the lack of a block verification...
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Cyber intrusion detection using dual interactive Wasserstein generative adversarial network with war strategy optimization in wireless sensor networks
Wireless sensor network (WSN) is one of the essential components of a multi-hop cyber-physical system comprising many fixed or moving sensors. There...
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Dual strategy for single image denoising and generation using deep neural network
Removing noise in the real-world scenario has been a daunting task in the field of natural language processing. Research has shown that Deep Neural...
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A method for recognizing facial expression intensity based on facial muscle variations
Expression intensity recognition is a research problem in the field of computer vision and pattern recognition, which can be understood as the...
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Multitask EfficientNet affective computing for student engagement detection
In the realm of education, feedback emerges as a pivotal component, serving to foster engagement and interaction while also facilitating the...
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Intelligent and efficient task caching for mobile edge computing
Given the problems with a centralized cloud and the emergence of ultra-low latency applications, and the needs of the Internet of Things (IoT), it...
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UDCT: lung Cancer detection and classification using U-net and DARTS for medical CT images
Lung cancer is the most fatal disease in recent times. Early detection of the same is very crucial and challenging task. Therefore, proper diagnostic...
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GSNR-aware resource re-provisioning for C to C+L-bands upgrade in optical backbone networks
Efficient network management in optical backbone networks is essential to manage continuous traffic growth. To accommodate this growth, network...
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A systematic review of factors, data sources, and prediction techniques for earlier prediction of traffic collision using AI and machine Learning
The prevalence of road traffic collisions is a pressing issue both worldwide and within the United States. The consequences of these incidents are...
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Research on a quantification model of online learning cognitive load based on eye-tracking technology
Online learning is characterized by a high degree of complexity and a wealth of information when compared to traditional classroom learning. This can...
