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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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Multimodal Information Retrieval
In today’s rapidly evolving digital landscape, the wealth of available information has expanded beyond the boundaries of traditional text-based...
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Retrieval Augmented Modeling
Till this point in our book, we have discussed the fundamental principles of information retrieval, exploring its key elements, and various...
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Outlook
While multimodal information retrieval has several exciting applications and a high potential for impact on important problems, there are several...
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Multimodal Content Generation
In this chapter, we will review the advances that are being made in this new field of multimodal content generation and also discuss several...
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Transformer-Driven Models for Language, Vision, and Multimodality
In this chapter, we will learn about the modeling and learning techniques that drive multimodal applications. We will focus specifically on the...
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Introduction
In this book, our emphasis is on multimodal information retrieval, specifically concentrating on text and image data. The traditional unimodal...
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Enhancing Cognition Through Cooperative Learning and Augmented Mentorship
With increasing cybercrime, educational institutions are working to create increased opportunities for people to enter the cyber workforce. Some...
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Assessment of a Novel Virtual Environment for Examining Cognitive-Motor Processes During Execution of Action Sequences in a Human-Robot Teaming Context
With the development of advanced AI and robotic systems, there is a growing interest in examining human-robot teaming. While the vast majority of...
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Early Use of Augmented Cognition for Online Learning Games in Hawai‘i
This paper provides a historical and regional perspective on the adoption of technologies in online learning, focusing on gamification as an aspect...
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Distance-Based Lifestyle Medicine for Veterans with Chronic Multi-symptom Illness (CMI): Health Coaching as Behavioral Health Intervention for Clinical Adherence
Chronic multi-symptom illness (CMI) is characterized by persistent, difficult to treat symptoms that interfere with daily functioning, affecting...
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Can Neurofeedback Training Decrease Cognitive Bias? An Exploratory Analysis
Cognitive biases are ubiquitous and finding ways to mitigate them has been an ongoing challenge. Here, we explore the possibility that brain training...