Designing a useful feature map for a quantum kernel is a critical task when attempting to achieve an advantage over classical machine learning models. The choice of circuit architecture, i.e. how feature-dependent gat...
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ISBN:
(纸本)9798331541378
Designing a useful feature map for a quantum kernel is a critical task when attempting to achieve an advantage over classical machine learning models. The choice of circuit architecture, i.e. how feature-dependent gates should be interwoven with other gates is a relatively unexplored problem and becomes very important when using a model of quantum kernels called Quantum Embedding Kernels (QEK). We study and categorize various architectural patterns in QEKs and show that existing architectural styles do not behave as the literature supposes. We also produce a novel alternative architecture based on the old ones and show that it performs equally well while containing fewer gates than its older counterparts.
The proliferation of Artificial Intelligence (AI), academic landscapes in research and learning are shifting from traditional to innovative strategies, greatly impacting students’ learning and teachers’ pedagogies i...
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During the pandemic era, there has been a sharp increase in online activity in the world of education as well as changes in the teaching system which tend to be hybrid, which also has an impact on learning strategies ...
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At the age of artificial intelligence, the inheritance and development of innovation culture are crucial for constructing an innovative country, and they are major components of cultural intelligence computing. The po...
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E-learning systems improve day by day. Therefore, it is important to monitor and evaluate student performance to provide targeted content. This paper focuses on a model for intelligent E-learning systems that can iden...
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The emerging of Digital Twin (DT) technology facilitates the further development of industrial automation. However, real-time and accurate DTs modeling and updating require massive communication and computing resource...
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ISBN:
(纸本)9798350358513;9798350358520
The emerging of Digital Twin (DT) technology facilitates the further development of industrial automation. However, real-time and accurate DTs modeling and updating require massive communication and computing resources, which poses a challenge to limited resources. Edge computing as a distributed computing architecture offers the possibility of high-efficient resource scheduling in DTs. Motivated by this gap, this paper aim to solve the problem of real-time and high fidelity DTs modeling and updating. First, we represent the computing tasks of DTs in the form of Heterogeneous computing Task Graph (HCTG). Then, a Hierarchical Attention Mechanism (HAT) is proposed to obtain the latent representation vectors of the HCTG. Finally, we design Markov Decision Process (MDP), and propose Deep Reinforcement learning (DRL)-based computing task scheduling approach (HAT-DRL) to satisfy the minimum total completion time requirement of different DTs. Experimental results demonstrate that the proposed algorithm has promising scheduling performance and outperforms other task scheduling algorithms.
The proceedings contain 51 papers. The special focus in this conference is on Social computing and Social Media. The topics include: A Serious Game Approach for teaching Requirements engineering: User Experience ...
ISBN:
(纸本)9783031935381
The proceedings contain 51 papers. The special focus in this conference is on Social computing and Social Media. The topics include: A Serious Game Approach for teaching Requirements engineering: User Experience Evaluation;identification of Older Adults’ Characteristics that Affect the Usability of Mobile Applications: A Tertiary Study;generating Product Descriptions Using Customer Reviews on E-Commerce Sites;improving Intention Recognition Efficiency: A Study on Skeletal Data Dimensionality Reduction and Neural Architectures;first Steps Toward the Agile Integration of Information Architecture into a User-Centered Development Process;LLM-Driven Augmented Reality Puppeteer: Controller-Free Voice-Commanded Robot Teleoperation;redimensioning Visible learning and teaching in the Dynamics of a New Reality;Generative AI in Education: Exploring EAP Faculty Perspectives at a Multicultural UAE University;the Challenges Faced by Albanian Teachers in the Use of Media Technology During teaching;Undergraduate Students’ Journey with AI in the United Arab Emirates;Perspectives of Faculty on the Easiness and Usefulness of AI Tutoring Systems in Higher Education;exploring the Use of Paraphrasing Tools in Academic Writing and Its Potential Relation with Instances of Plagiarism;a Property Checklist for Evaluating the Student Experience with Consideration of Cultural Aspects;human-Robot Interaction in Higher Education: A Literature Review;artificial Intelligence in Higher Education: Student Perceptions of the Adoption and Integration in Ghana, West Africa;a Management Model for Evaluating Scientific Productivity in Chilean Universities: A Case Analysis;virtual Reality Meets Social Media: Transforming Skill Acquisition in Physiotherapy, Veterinary Surgery, and Driver Training;Evolution of Emotional Response of PLEA—An Embodied Virtual Being with Emotional Capabilities.
Neuromorphic computing is a new paradigm that emerges from the structure and function of the human brain and aims to revolutionize computing. The technology is designed to simulate the high speed, low power consumptio...
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According to the actual needs of students majoring in vehicle engineering, this paper focuses on the application of virtual simulation experimental environment in their professional learning and ability training. Thro...
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Linear systems of equations can be found in various mathematical domains, as well as in the field of machine learning. By employing noisy intermediate-scale quantum devices, variational solvers promise to accelerate f...
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ISBN:
(纸本)9798331541378
Linear systems of equations can be found in various mathematical domains, as well as in the field of machine learning. By employing noisy intermediate-scale quantum devices, variational solvers promise to accelerate finding solutions for large systems. Although there is a wealth of theoretical research on these algorithms, only fragmentary implementations exist. To fill this gap, we have developed the variational-lse-solver framework, which realizes existing approaches in literature, and introduces several enhancements. The user-friendly interface is designed for researchers that work at the abstraction level of identifying and developing end-to-end applications.
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