The proceedings contain 9 papers. The special focus in this conference is on AI Verification. The topics include: Concept-Based Analysis of Neural networks via Vision-Language Models;parallel Verification fo...
ISBN:
(纸本)9783031651113
The proceedings contain 9 papers. The special focus in this conference is on AI Verification. The topics include: Concept-Based Analysis of Neural networks via Vision-Language Models;parallel Verification for δ-Equivalence of Neural Network Quantization;verification of Neural Network Control systems in Continuous Time;a Preliminary Study to Examining Per-class Performance Bias via Robustness Distributions;clover: Closed-Loop Verifiable Code Generation;provable Repair of Vision Transformers;iterative Counter-Example Guided Robustness Verification for Neural networks.
Medical Named Entity Recognition (NER) plays a crucial role in enhancing the efficiency of clinical work. Currently, Chinese Named Entity Recognition methods based on deep learning models have shown significant result...
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Federated learning (FL) has been envisioned as a promising distributed learning framework for next-generation wireless communication systems. FL introduces new challenges in system design, since users need to consider...
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ISBN:
(纸本)9781665464833
Federated learning (FL) has been envisioned as a promising distributed learning framework for next-generation wireless communication systems. FL introduces new challenges in system design, since users need to consider the local processing optimization in addition to traditional communication resources allocation. In this paper, we aim to address this challenge by considering a wireless-powered FL network with multiple users, where non-orthogonal multiple access (NOMA) is employed for uplink transmission. A latency minimization problem is formulated, requiring to jointly optimize the power and time allocation for all FL phases together with the local processing computation frequency at each user. An one-dimensional search algorithm (ODSA) is proposed to obtain the optimal solution for the formulated non-convex problem. Presented numerical results demonstrate that the proposed scheme outperforms its orthogonal counterpart.
The number of mobile devices is rapidly outgrowing the current world population, making them the most popular medium to communicate and share information. In addition, applications that enable communication and data s...
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ISBN:
(纸本)9783031352591;9783031352607
The number of mobile devices is rapidly outgrowing the current world population, making them the most popular medium to communicate and share information. In addition, applications that enable communication and data sharing still heavily rely on centralized networks. We believe that this problem is mainly due to the lack of tools to help programmers develop and test applications with many devices in edge environments. To help programmers develop and test such distributed applications, we propose EdgeEmu, an Android distributed emulation testbed for mobile applications. EdgeEmu supports a high number of Android emulators participating in a large network by allowing them to remotely participate in the emulation, thus removing the scalability bottleneck that current Android testing infrastructure has. EdgeEmu is, therefore, not limited to locally deployed emulators as opposed to the standard Android SDK. To study the performance of EdgeEmu, extensive evaluation through different scenarios has been conducted. Results demonstrate that EdgeEmu outperforms the standard Android SDK by approximately 59.1% in terms of emulation startup time when ten Android emulators are used. Evaluations also show promising results for low latency and negligible overhead when sending messages to and from different emulators.
Collective communication primitives (CCPs), such as multicast and broadcast, are essential for many parallel and distributed applications. In response, this study compares a topology-oblivious algorithm underlying the...
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In the context of the construction of new power systems, there is an urgent need for true testing and verification of new fault self-healing algorithms for active distribution networks with a large number of distribut...
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Local interactions of uncoordinated individuals produce the collective behaviors of many biological systems, inspiring much of the current research in programmable matter. A striking example is the spontaneous assembl...
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Federated learning is a type of technique that makes it possible to train the models using a centralized process, at the same time ensuring that individual privacy is observed. We also propose the Federated Gradient F...
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Network analysis and visualization are crucial for unraveling complex relationships across diverse fields, from social networks to biological systems. NodeXL is a versatile network analysis tool that supports a wide r...
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distributed photovoltaic power supply exhibits cost-effectiveness, simplified installation procedures, reduced expenses, independence from terrain limitations, thereby augmenting its share in the distribution network ...
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