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Spatial-Temporal Knowledge Transfer for Dynamic Constrained Multiobjective Optimization

IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： Wang, Zhenzhong Xu, Dejun Jiang, Min Tan, Kay Chen Department of Computing The Hong Kong Polytechnic University Hong Kong P.R. China Department of Artificial Intelligence Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism School of Informatics Xiamen University Xiamen Fujian China Department of Data Science and Artificial Intelligence The Hong Kong Polytechnic University Hong Kong P.R. China

Dynamic Constrained Multiobjective Optimization Problems (DCMOPs) are characterized by multiple conflicting optimization objectives and constraints that vary over time. The presence of both dynamism and constraints underscores the importance of preserving population diversity. This diversity is essential not only to escape local optima following environmental changes but also to climb infeasible barriers to approach feasible regions. However, existing constraint-handling techniques for enhancing solution feasibility could steer infeasible solutions toward partially feasible regions, potentially resulting in the loss of diversity. To maintain both diversity and feasibility, this work establishes two synergistic tasks: one task concentrates on exploring the unconstrained search space to preserve diversity, while the other delves into searching the constrained search space to prioritize feasibility. Particularly, in light of evolutionary transfer optimization, two knowledge transfer modules, i.e., the spatial knowledge transfer module and temporal knowledge transfer module are designed. The spatial knowledge transfer module facilitates knowledge transfer between the constrained and unconstrained search spaces to accelerate the exploration of both spaces. On the other hand, the temporal transfer module leverages historical knowledge to enhance search efficiency within the new environment. To advance the test suite toward real-world cases, we designed fourteen test problems with various properties. Experiments conducted on the proposed test problems and a real-world problem have demonstrated the efficacy of our proposed algorithm. IEEE

关键词： Constrained optimization

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SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation

SpreadFGL: Edge-Client Collaborative Federated Graph Learnin...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Luying Zhong Yueyang Pi Zheyi Chen Zhengxin Yu Wang Miao Xing Chen Geyong Min College of Computer and Data Science Fuzhou University China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University China Engineering Research Center of Big Data Intelligence Ministry of Education China School of Computing and Communications University of Lancaster UK School of Engineering Computing and Mathematics University of Plymouth UK Department of Computer Science University of Exeter UK

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Federated Graph Learning (FGL) has garnered widespread attention by enabling collaborative training on multiple clients for semi-supervised classification tasks. However, most existing FGL studies do not well consider the missing inter-client topology information in real-world scenarios, causing insufficient feature aggregation of multi-hop neighbor clients during model training. Moreover, the classic FGL commonly adopts the FedAvg but neglects the high training costs when the number of clients expands, resulting in the overload of a single edge server. To address these important challenges, we propose a novel FGL framework, named SpreadFGL, to promote the information flow in edge-client collaboration and extract more generalized potential relationships between clients. In SpreadFGL, an adaptive graph imputation generator incorporated with a versatile assessor is first designed to exploit the potential links between subgraphs, without sharing raw data. Next, a new negative sampling mechanism is developed to make SpreadFGL concentrate on more refined information in downstream tasks. To facilitate load balancing at the edge layer, SpreadFGL follows a distributed training manner that enables fast model convergence. Using real-world testbed and benchmark graph datasets, extensive experiments demonstrate the effectiveness of the proposed SpreadFGL. The results show that SpreadFGL achieves higher accuracy and faster convergence against state-of-the-art algorithms.

关键词： Training Accuracy Collaboration Benchmark testing Imputation Generators Topology

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Tiny Object Tracking: A Large-scale Dataset and A Baseline

arXiv

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arXiv 2022年

作者： Zhu, Yabin Li, Chenglong Liu, Yao Wang, Xiao Tang, Jin Luo, Bin Huang, Zhixiang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing Anhui Higher Education Institutes Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Hefei230601 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China School of Computer Science and Technology Anhui University Hefei230601 China Peng Cheng Laboratory Shenzhen China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing Anhui Higher Education Institutes Anhui University Hefei230601 China

Tiny objects, frequently appearing in practical applications, have weak appearance and features, and receive increasing interests in meany vision tasks, such as object detection and segmentation. To promote the research and development of tiny object tracking, we create a large-scale video dataset, which contains 434 sequences with a total of more than 217K frames. Each frame is carefully annotated with a high-quality bounding box. In data creation, we take 12 challenge attributes into account to cover a broad range of viewpoints and scene complexities, and annotate these attributes for facilitating the attribute-based performance analysis. To provide a strong baseline in tiny object tracking, we propose a novel Multilevel Knowledge Distillation Network (MKDNet), which pursues three-level knowledge distillations in a unified framework to effectively enhance the feature representation, discrimination and localization abilities in tracking tiny objects. Extensive experiments are performed on the proposed dataset, and the results prove the superiority and effectiveness of MKDNet compared with state-of-the-art methods. The dataset, the algorithm code, and the evaluation code are available at https://***/mmic-lcl/Datasets-andbenchmark-code. Copyright © 2022, The Authors. All rights reserved.

关键词： Distillation

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High Transmittance Band-Pass Plasmonic Filter Using Metal-Insulator-Metal Waveguide with Double Split Circular Ring Resonator

High Transmittance Band-Pass Plasmonic Filter Using Metal-In...

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Hui Wang Yi-yang Huang San-wang Ma Chun Ni Zhi-xiang Huang Xian-liang Wu Anhui Province Key Laboratory of Target Recognition and Feature Extraction Lu'an China Anhui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

ISBN: (纸本)9781665482271

In this paper, a band-pass plasmonic filter based on Metal-Insulator-Metal (MIM) waveguides and its modified structures are designed and investigated theoretically and numerically. The filter consists of two circular ring resonator and its modified structures which has narrow gaps in the middle of resonant rings. To study their performance in different structures, propagation modes of surface plasmon polaritons (SPPs) are investigated. In outer gapped model, we found that the transmission in different resonant modes can be effectively tuned by varying the gap width, and the transmission peak wavelength is nonlinear with the gap width. The results are obtained by high-order symplectic FDTD (SFDTD) algorithm which is non-dissipative and has low dispersion error. The structure with double gaps in both external and internal rings have potential applications in plasmonic integrated circuits, because of its characteristic of a single narrow band-pass with high transmittance. The introduced structures may provide a novel method for the design of devices in highly integrated optical circuits.

关键词： Band-pass filters Optical filters Structural rings Integrated optics Resonator filters Plasmons Optical ring resonators

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Singular Value Decomposition Compressed Ghost Imaging Based on Non-negative Constraints 11

Singular Value Decomposition Compressed Ghost Imaging Based ...

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2019第十一届数字图像处理国际会议

作者： Cheng Zhang Jun Tang Yuanyuan Zhu Meiqin Wang Qianwen Chen Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

ISBN: (数字)9781510630765

ISBN: (纸本)9781510630758

Compressed ghost imaging can effectively enhance the quality of original image from far fewer measurements,but due to the non-negativity of the measurement matrix,the recover quality is thus *** this paper,singular value decomposition compressed ghost imaging is proposed;First,the singular value decomposition be used to decompose the measurement matrix,and then the optimized measurement matrix and measurements are used to recover the original *** experiments verify the superiority of our proposed singular value decomposition compression ghost imaging method.

关键词： ghost imaging compressed ghost imaging singular value decomposition compressed ghost imaging

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A Simple Single-Fed Penta-Band Omnidirectional Antenna with Independent Band Control

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IEEE Transactions on Antennas and Propagation 2025年

作者： Zhou, Changfei Gao, Tianyu Zhang, Ruyue Yu, Dapeng Zhang, Wenyu Li, Yingsong Wong, Hang Dalian University of Technology School of Information and Communication Engineering Dalian116024 China Hubei University of Automotive Technology School of Mathematics Physics and Optoelectronic Engineering Shiyan China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China City University of Hong Kong The State Key Laboratory of Terahertz and Millimeter Waves Hong Kong

A novel method of designing a penta-band omnidirectional low-profile antenna with independent band control is proposed. Single-band, dual-band, tri-band, quad-band, and penta-band antennas are investigated, respectively. The proposed penta-band antenna consists of a circular patch, three concentric metal pins, and two square metal plates. The evolutionary step of the penta-band antenna is achieved by adding metal rings and a small metal plate above the big ground. Each of the four metal rings is excited at TM01 mode resonance, while the 5th mode is generated by a small loop resonance formed by the small plate, shorting pin, stub, and the outer conductor of the cable. The penta-band antenna has a small volume of π × (0.109λ1.53GHz)2 × 0.053λ1.53GHz. The corresponding impedance bandwidths (IMBWs) of the five operating bands are 4.9%, 9.4%, 9.0%, 4.8%, 5.0%. Compared with other designs, the proposed antennas exhibit more flexible bands by using a simple structure. Meanwhile, the antenna has a stable omnidirectional radiation pattern across the five bands and a compact size. © 1963-2012 IEEE.

关键词： Monopole antennas

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Community Evolution Tracking Based on Core Node Extension and Edge Variation Discerning 17th

Community Evolution Tracking Based on Core Node Extension a...

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17th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2022

作者： Zhuang, Qifeng Yu, Zhiyong Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350108 China Key Laboratory of Spatial Data Mining and Information Sharing Ministry of Education Fuzhou350108 China

ISBN: (纸本)9789819923557

Communities exist anywhere in various complex networks, and community evolution tracking is one of the most well-liked areas of inquiry in the study of dynamic complex networks. Community evolution tracking has many applications in daily life, such as predicting social network behaviors or analyzing the spread of infectious illnesses. However, the majority of existing evolution tracking algorithms obtain community detection results before matching the community in tracking evolution events, making it difficult to trace the whole evolution of communities because of community matching errors. In addition, the majority of evolution tracking algorithms do not adequately account for the potential scenarios in community evolution, resulting in erroneous detection of evolution events. In this research, a community evolution tracking algorithm based on edge variation discerning and core node extension is proposed. First, we detect communities based on the core node extension strategy, which avoids the problem of community matching errors. Second, we track community evolution based on the edge variation discerning strategy, which fully considers various situations that may occur during the community evolution process. According to the outputs of our experiments, our system can effectively track the evolution of communities in synthetic dynamic networks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Complex networks

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Robust DOA Estimation Against Outliers via Joint Sparse Representation

TechRxiv

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TechRxiv 2023年

作者： Li, Yingsong Xiao, Wudang Zhao, Luyu Huang, Zhixiang Li, Qiang Li, Liping de Lamare, Rodrigo C. Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei230601 China PUC-Rio Brazil University of York United Kingdom Gávea 22451-900 Brazil Department of Electronic Engineering University of York YorkYO10 5DD United Kingdom

Standard Direction of Arrival (DOA) estimation methods are typically derived based on the Gaussian noise assumption, making them highly sensitive to outliers. Therefore, in the presence of impulsive noise, the performance of these methods may significantly deteriorate. In this paper, we model impulsive noise as Gaussian noise mixed with sparse outliers. By exploiting their statistical differences, we propose a novel DOA estimation method based on sparse signal recovery (SSR). Furthermore, to address the issue of grid mismatch, we utilize an alternating optimization approach that relies on the estimated outlier matrix and the on-grid DOA estimates to obtain the off-grid DOA estimates. Simulation results demonstrate that the proposed method exhibits robustness against large outliers. © 2023, CC BY.

关键词： Direction of arrival

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Coherence-Based Distributed Document Representation Learning for Scientific Documents

arXiv

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arXiv 2022年

作者： Tan, Shicheng Zhao, Shu Zhang, Yanping Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui Province 230601 China School of Computer Science and Technology Anhui University Anhui Province Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Province 230601 China

Distributed document representation is one of the basic problems in natural language processing. Currently distributed document representation methods mainly consider the context information of words or sentences. These methods do not take into account the coherence of the document as a whole, e.g., a relation between the paper title and abstract, headline and description, or adjacent bodies in the document. The coherence shows whether a document is meaningful, both logically and syntactically, especially in scientific documents (papers or patents, etc.). In this paper, we propose a coupled text pair embedding (CTPE) model to learn the representation of scientific documents, which maintains the coherence of the document with coupled text pairs formed by segmenting the document. First, we divide the document into two parts (e.g., title and abstract, etc) which construct a coupled text pair. Then, we adopt negative sampling to construct uncoupled text pairs whose two parts are from different documents. Finally, we train the model to judge whether the text pair is coupled or uncoupled and use the obtained embedding of coupled text pairs as the embedding of documents. We perform experiments on three datasets for one information retrieval task and two recommendation tasks. The experimental results verify the effectiveness of the proposed CTPE model. Copyright © 2022, The Authors. All rights reserved.

关键词： Information retrieval

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Ask, attend, attack: an effective decision-based black-box targeted attack for image-to-text models 24

Ask, attend, attack: an effective decision-based black-box t...

引用

Proceedings of the 38th International Conference on Neural Information processing Systems

作者： Qingyuan Zeng Zhenzhong Wang Yiu-ming Cheung Min Jiang Department of Artificial Intelligence Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University Xiamen Fujian P.R. China Department of Computing The Hong Kong Polytechnic University Department of Computer Science Hong Kong Baptist University School of Informatics Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen University Xiamen Fujian P.R. China

ISBN: (纸本)9798331314385

While image-to-text models have demonstrated significant advancements in various vision-language tasks, they remain susceptible to adversarial attacks. Existing white-box attacks on image-to-text models require access to the architecture, gradients, and parameters of the target model, resulting in low practicality. Although the recently proposed gray-box attacks have improved practicality, they suffer from semantic loss during the training process, which limits their targeted attack performance. To advance adversarial attacks of image-to-text models, this paper focuses on a challenging scenario: decision-based black-box targeted attacks where the attackers only have access to the final output text and aim to perform targeted attacks. Specifically, we formulate the decision-based black-box targeted attack as a large-scale optimization problem. To efficiently solve the optimization problem, a three-stage process Ask, Attend, Attack, called AAA, is proposed to coordinate with the solver. Ask guides attackers to create target texts that satisfy the specific semantics. Attend identifies the crucial regions of the image for attacking, thus reducing the search space for the subsequent Attack. Attack uses an evolutionary algorithm to attack the crucial regions, where the attacks are semantically related to the target texts of Ask, thus achieving targeted attacks without semantic loss. Experimental results on transformer-based and CNN+RNN-based image-to-text models confirmed the effectiveness of our proposed AAA.

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