检索结果-内蒙古大学图书馆

7th International Conference on Machine Learning and Natural Language Processing, MLNLP 2024

作者： Feng, Bo Yan, Xi Yan, Li Luo, Bing Pei, Zheng School of Science Xihua University Chengdu China School of Computer Science and Software Engineering Xihua University Chengdu China

ISBN: (纸本)9798350354973

The integration of the contrastive learning paradigm into deep clustering has led to enhanced performance in image clustering. However, in existing researches, the samples in the class of the target may be still treated as negative samples, this means that more semantic sample pairs cannot be constructed and the intra-class compactness may be compromised. In this paper, we propose a new contrastive clustering method based on mining latent positive samples (CCLPS), which utilizes the nearest neighbor relationship between samples to mine semantic positive samples in the same class. In more detail, by mining latent positive samples in both the feature and cluster spaces, CCLPS can obtain more cluster-friendly feature representation of samples to enhance clustering performance. Samples mined from the feature space fuel the cluster-level contrastive learning task, while samples mined from the cluster space fuel the instance-level task. Three image datasets CIFAR-10, CIFAR-100 and Tiny-ImageNet are employed to experimentally demonstrate usefulness and effectiveness of the proposed method in image clustering, and transfer learning based on mining latent positive samples is also discussed and comparisons are made with 19 representative clustering methods on the datasets. Experimental results indicate that the proposed method can serve as a pre-training model for transfer learning and exhibits commendable feature modeling capabilities. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Entropy-based Selective Homomorphic Encryption for Smart Metering Systems 28

Entropy-based Selective Homomorphic Encryption for Smart Met...

引用

28th IEEE Pacific Rim International Symposium on Dependable Computing, PRDC 2023

作者： Xu, Weiyan Zhang, Yinghao Cardell-Oliver, Rachel Mian, Ajmal Hong, Jin B. The University of Western Australia Department of Computer Science and Software Engineering Australia

ISBN: (纸本)9798350358766

Smart metering systems (SMS) are popular in industrial and residential areas but can risk privacy by revealing user behaviors. Homomorphic encryption (HE) is a technique that protects data privacy by enabling calculations on encrypted data. However, the high computational costs of HE can hinder real-time or resource-constrained applications. Our paper presents a framework to encrypt only selected SMS data for improved efficiency without compromising privacy significantly. By encrypting data blocks with higher entropy values, we can mitigate the leakage of key information to adversaries who may conduct privacy attacks, such as membership inference attacks (MIA). We evaluate our framework using two real-world datasets (i.e., electricity and water) to assess privacy and performance trade-offs. The results indicate a 47% performance increase while still providing a sufficient level of privacy when adopting an encryption ratio of 0.4. They demonstrate the effectiveness of the proposed framework, considering the trade-off between privacy and performance, where the user can determine the appropriate security level for privacy protection and enhance the performance using HE in practical SMS settings. © 2023 IEEE.

关键词： Entropy

来源：评论

学校读者我要写书评

暂无评论

Multichannel Seismic Deconvolution via 2D K-SVD and Convolutional Sparse Coding 3

Multichannel Seismic Deconvolution via 2D K-SVD and Convolut...

引用

3rd International Meeting for Applied Geoscience and Energy, IMAGE 2023

作者： Zhang, Guiqian Gao, Xiayu Zou, Bangli Wang, Yaojun Chen, Yingzhu China College of Computer Science and Software Engineering Shenzhen University China

Seismic deconvolution encounters problems of multiplicity and instability. The regularization technique based on various prior knowledge is used to constrain the range of solutions and improve the stability of deconvolution results. We use dictionary learning as a technical means to consider both vertical resolution and lateral continuity issues in reflectivity inversion problem. Considering the drawbacks of patch-based operations in 1D dictionary learning, we adopt 2D K-SVD and convolutional sparse coding (CSC) based on global feature extraction as the dictionary learning methods. We divide the seismic profile into low-frequency component and high-frequency component, and reconstruct their corresponding reflectivity with 2D K-SVD and CSC, respectively. Finally, the seismic deconvolution with high resolution and strong continuity is obtained by summing the results of each component deconvolution. The effectiveness of the proposed method is verified by Marmousi model data. © 2023 Society of Exploration Geophysicists and the American Association of Petroleum Geologists.

关键词： Reflection

来源：评论

学校读者我要写书评

暂无评论

SOID: Towards an Efficient Incremental Deployment Scheme for Source Address Validation 29

SOID: Towards an Efficient Incremental Deployment Scheme for...

引用

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Yang, Shu Song, Bingqian Cui, Laizhong Shenzhen University College of Computer Science and Software Engineering Shenzhen China

ISBN: (纸本)9798350330717

The current Internet makes forwarding decisions based on only destination addresses, leading to a prevalence of IP source address spoofing. To mitigate the risks posed by IP spoofing, Source Address Validation in Intra-domain and Interdomain Networks (SAVNET) has been recently proposed and become a hot topic in both academia and industry. While all network equipment can not be upgraded to support SAVNET during one night, incremental deployment is needed for network operators. However, SAVNET can not defend against all spoofing attacks under partial deployment. Thus, we need to carefully choose nodes to be deployed, to improve incentive benefits during incremental deployment. In this paper, we formulate the incremental problem and prove that the problem is NP-Complete. To efficiently solve the problem, we propose a heuristic deployment scheme named SOID (SAV protocol optimized incremental deployment). The intuitive idea of SOID is using the sink-tree to get the detectable flow sets of each router. Then, it selects the routers which have the maximum total weight during each iteration. To evaluate the performance of the proposed algorithm, we conduct comprehensive simulations with generated and real topologies. The simulation results show that SOID performs much better compared with traditional schemes, such as random deployment and minimum vertex cover algorithms, with a manageable overhead. © 2023 IEEE.

关键词： Incremental Deployment Algorithm Intra-domain Source Address Validation

来源：评论

学校读者我要写书评

暂无评论

A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs

引用

computers, Materials & Continua 2024年第8期80卷 1831-1850页

作者： Hina Gul Sana Ullah Ki-Il Kim Farman Ali Department of Computer and Software Technology University of SwatMingora19130Pakistan Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Republic of Korea Department of Applied AI Sungkyunkwan UniversitySeoul03063Republic of Korea

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart *** and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of *** paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such *** proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual *** protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base *** performance of the proposed protocol is evaluated through the network simulator *** different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network *** 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.

关键词： Internet of Things wireless sensor networks traffic load clustering routing energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Impact of Feature Encoding on Malware Classification Explainability 15

Impact of Feature Encoding on Malware Classification Explain...

引用

15th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2023

作者： Manai, Elyes Mejri, Mohamed Fattahi, Jaouhar Laval University Department of Computer Science & Software Engineering Quebec Canada

ISBN: (纸本)9798350321388

This paper investigates the impact of feature encoding techniques on the explainability of XAI (Explainable Artificial Intelligence) algorithms. Using a malware classification dataset, we trained an XGBoost model and compared the performance of two feature encoding methods: Label Encoding (LE) and One Hot Encoding (OHE). Our findings reveal a marginal performance loss when using OHE instead of LE. However, the more detailed explanations provided by OHE compensated for this loss. We observed that OHE enables deeper exploration of details in both global and local contexts, facilitating more comprehensive answers. Additionally, we observed that using OHE resulted in smaller explanation files and reduced analysis time for human analysts. These findings emphasize the significance of considering feature encoding techniques in XAI research and suggest potential for further exploration by incorporating additional encoding methods and innovative visualization approaches. © 2023 IEEE.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

Container-Aware Service Function Chains Placement and Optimization in Vehicular Edge Computing 22

Container-Aware Service Function Chains Placement and Optimi...

引用

22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Zhang, Kaixin Hu, Shihong Qu, Zhihao Ye, Baoliu Hohai University School of Computer Science and Software Engineering China Nanjing University National Key Laboratory for Novel Software Technology China

ISBN: (纸本)9798331509712

In the domain of Vehicular Edge Computing (VEC), this paper addresses the complex problem of Service Function Chain (SFC) placement, which is crucial for the efficient deployment of cloud applications in vehicular environments. Our approach leverages Virtual Network Function (VNF) technology, transitioning network services from traditional hardware to more flexible, container-based edge computing frameworks. The primary objective is to organize these VNFs into functional SFCs, thereby minimizing service delays in VEC systems. SFC placement faces two significant challenges. The first is the sequential dependency among VNFs within an SFC, which adds substantial complexity to container deployment. The second challenge is the cold start delay of VNF containers, a critical issue in scenarios requiring swift response times, which negatively impacts service quality in VEC applications. To address these challenges, we propose a comprehensive model for SFC placement that considers the deployment status of VNF containers, acknowledging the complexity of this NP-hard problem. The core of our contribution is the development of the Single SFC Placement Algorithm (SSPA), a sophisticated, greedy-based approach designed for the effective placement of individual SFCs. We enhance this algorithm by incorporating a Particle Swarm Optimization (PSO) technique, making it capable of efficiently handling the placement of multiple SFCs. Our solution aims to improve edge resource utilization and mitigate startup delays associated with the initial activation of containers, thereby reducing service delays. Extensive experimental evaluations demonstrate that our algorithm achieves a 34.3% average reduction in service delay compared to four baselines and a 5.8% average reduction compared to other container-aware algorithms. © 2024 IEEE.

关键词： service function chain SFC placement vehicle edge computing virtual network function

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection in Dynamic Graphs Via Long Short-Term Temporal Attention Network

Anomaly Detection in Dynamic Graphs Via Long Short-Term Temp...

引用

2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Gao, Zu-Kang Ma, Le-Ming Li, Mei-Ting Zhao, Gen Li, Mark Jun-Jie College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9798350303780

Anomaly detection in dynamic graphs has drawn increasing attention in social networks, e-commerce, and cybersecurity etc. Capturing the evolution patterns using temporal features is crucial for dynamic graphs anomaly detection. However, existing approaches do not thoroughly consider the long-term and short-term temporal features, which lead to the loss of information about the evolution patterns of dynamic graphs. In this paper, we propose a end-to-end an anomaly detection algorithm in dynamic graphs via Long Short-term Temporal Attention network (GraphLSTA). GraphLSTA captures the evolution patterns of dynamic graphs by effectively extracting and fusing the long-term and short-term temporal features through a recurrent attention mechanism, improving the detection performance. © 2023 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

An Efficient and Fast Area Optimization Approach for Mixed Polarity Reed-Muller Logic Circuits

引用

Chinese Journal of Electronics 2024年第5期33卷 1165-1180页

作者： Yuhao ZHOU Zhenxue HE Jianhui JIANG Xiaojun ZHAO Fan ZHANG Limin XIAO Xiang WANG School of Software Engineering Tongji University Key Laboratory of Agricultural Big Data of Hebei Province Hebei Agricultural University School of Computer Science and Engineering Beihang University School of Electronic and Information Engineering Beihang University

Area has become one of the main bottlenecks restricting the development of integrated circuits. The area optimization approaches of existing XNOR/OR-based mixed polarity Reed-Muller(MPRM) circuits have poor optimization effect and efficiency. Given that the area optimization of MPRM logic circuits is a combinatorial optimization problem, we propose a whole annealing adaptive bacterial foraging algorithm(WAA-BFA), which includes individual evolution based on Markov chain and Metropolis acceptance criteria, and individual mutation based on adaptive probability. To address the issue of low conversion efficiency in existing polarity conversion approaches, we introduce a fast polarity conversion algorithm(FPCA). Moreover, we present an MPRM circuits area optimization approach that uses the FPCA and WAA-BFA to search for the best polarity corresponding to the minimum circuits area. Experimental results demonstrate that the proposed MPRM circuits area optimization approach is effective and can be used as a promising EDA tool.

关键词： Integrated circuits Microorganisms Annealing Logic circuits Circuits Benchmark testing Delays

来源：评论

学校读者我要写书评

暂无评论

LLMaaS: Serving Large-Language Models on Trusted Serverless Computing Platforms

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年第2期6卷 405-415页

作者： Cai, Zinuo Ma, Rongbo Fu, Yicheng Zhang, Weishan Ma, Ruhui Guan, Haibing Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Qingdao Institute of Software College of Computer Science and Technology Qingdao266555 China

In recent years, the emergence of large-language models (LLMs) has profoundly transformed our production and lifestyle. These models have shown tremendous potential in fields, such as natural language processing, speech recognition, and recommendation systems, and are increasingly playing crucial roles in applications such as human-computer interaction and intelligent customer service. Efficient inference solutions for LLMs in data centers have been extensively researched, with a focus on meeting users' quality of service requirements. In this article, we focus on two additional requirements that responsible LLM inference should meet under QoS conditions: security throughout the model execution process and low maintenance requirements for the inference system. Therefore, we propose LLMaaS, a trusted model inference platform based on a serverless computing platform aimed at providing inference as a service for LLMs. First, we design a trusted serverless computing platform based on software guard extension (SGX), which includes distributed identity verification and SGX device plugins to ensure the security and trustworthiness of the inference process. Additionally, to reduce the maintenance requirements of the system, we enhance the SGX-based deep learning computing framework, including replacing PyTorch and using a greedy algorithm for graph partitioning. We conduct tests on four typical large models, and the experimental results demonstrate that, with minimal overhead and user code modifications, we can ensure the security of model execution. © 2020 IEEE.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：