检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Chen, Zhenyu Lin, Lijinzhi Lin, Xiaodie Wei, Zhaohui Yao, Penghui Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Department of Computer Science and Technology Tsinghua University Beijing100084 China Yau Mathematical Sciences Center Tsinghua University Beijing100084 China Yanqi Lake Beijing Institute of Mathematical Sciences and Applications 101407 China State Key Laboratory for Novel Software Technology Nanjing University Jiangsu Province Nanjing210023 China Hefei National Laboratory Hefei230088 China

Suppose two separated parties, Alice and Bob, share a bipartite quantum state or a classical correlation called a seed, and they try to generate a target classical correlation by performing local quantum or classical operations on the seed, i.e., any communications are not allowed. We consider the following fundamental problem about this setting: whether Alice and Bob can use a given seed to generate a target classical correlation. We show that this problem has rich mathematical structures. Firstly, we prove that even if the seed is a pure bipartite state, the above decision problem is already NP-hard and a similar conclusion can also be drawn when the seed is also a classical correlation, implying that this problem is hard to solve generally. Furthermore, we prove that when the seed is a pure quantum state, solving the problem is equivalent to finding out whether the target classical correlation has some diagonal form of positive semi-definite factorizations that matches the seed pure state, revealing an interesting connection between the current problem and optimization theory. Based on this observation and other insights, we give several necessary conditions where the seed pure state has to satisfy to generate the target classical correlation, and it turns out that these conditions can also be generalized to the case that the seed is a mixed quantum state. Lastly, since diagonal forms of positive semi-definite factorizations play a crucial role in solving the problem, we develop an algorithm that can compute them for an arbitrary classical correlation, which has decent performance on the cases we test. © 2023, CC BY.

关键词： Factorization

来源：评论

学校读者我要写书评

暂无评论

Quantum Algorithm for Fidelity Estimation

arXiv

引用

arXiv 2021年

作者： Wang, Qisheng Zhang, Zhicheng Chen, Kean Guan, Ji Fang, Wang Liu, Junyi Ying, Mingsheng The Department of Computer Science and Technology Tsinghua University Beijing China Centre for Quantum Software and Information University of Technology Sydney Australia The University of Chinese Academy of Sciences China The State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

For two unknown mixed quantum states ρ and σ in an N -dimensional Hilbert space, computing their fidelity F (ρ, σ) is a basic problem with many important applications in quantum computing and quantum information, for example verification and characterization of the outputs of a quantum computer, and design and analysis of quantum algorithms. In this paper, we propose a quantum algorithm that solves this problem in poly(log(N), r, 1/Ε) time, where r is the lower rank of ρ and σ, and Ε is the desired precision, provided that the purifications of ρ and σ are prepared by quantum oracles. This algorithm exhibits an exponential speedup over the best known algorithm (based on quantum state tomography) which has time complexity polynomial in N. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum optics

来源：评论

学校读者我要写书评

暂无评论

Time-Aware Missing Traffic Flow Prediction for Sensors with Privacy-Preservation

Time-Aware Missing Traffic Flow Prediction for Sensors with ...

引用

作者： Lianyong Qi Fan Wang Xiaolong Xu Wanchun Dou Xuyun Zhang Mohammad R.Khosravi Xiaokang Zhou School of Computer Science Qufu Normal University School of Computer and Software Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Department of Computing Macquarie University Department of Computer Engineering Persian Gulf University Department of Electrical and Electronic Engineering Shiraz University of Technology Faculty of Data Science Shiga University

With the continuous development of Io T, a number of sensors establish on the roadside to monitor traffic conditions in real time. The continuously traffic data generated by these sensors makes traffic management feasible. However, loss of data may occur due to inevitable sensor failure, impeding traffic managers to understand traffic dynamics clearly. In this situation, it is becoming a necessity to predict missing traffic flow accurately for effective traffic management. Furthermore, the traffic sensor data are often distributed and stored by different agencies,which inhibits the multi-party sensor data sharing significantly due to privacy concerns. Therefore, it has become a major obstacle to balance the tradeoff between data sharing and vehicle privacy. In light of these challenges, we propose a privacyaware and accurate missing traffic flow prediction approach based on time-aware Locality-Sensitive Hashing technique. At last, we deploy a set of experiments based on a real traffic dataset. Experimental reports demonstrate the feasibility of our proposal in terms of traffic flow prediction accuracy and efficiency while guaranteeing sensor data privacy.

关键词： Traffic flow prediction Multi-party sensors Privacy Locality-Sensitive Hashing

来源：评论

学校读者我要写书评

暂无评论

Relational proofs for quantum programs

Relational proofs for quantum programs

引用

Proceedings of the ACM on Programming Languages

作者： Barthe, Gilles Hsu, Justin Ying, Mingsheng Yu, Nengkun Zhou, Li Max Planck Institute for Security and Privacy Germany IMDEA Software Institute Spain Department of Computer Sciences University of Wisconsins Madison United States Centre for Quantum Software and Information University of Technology Sydney Australia State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Tsinghua University China Department of Computer Science and Technology Tsinghua University China

Relational verification of quantum programs has many potential applications in quantum and post-quantum security and other domains. We propose a relational program logic for quantum programs. The interpretation of our logic is based on a quantum analogue of probabilistic couplings. We use our logic to verify non-trivial relational properties of quantum programs, including uniformity for samples generated by the quantum Bernoulli factory, reliability of quantum teleportation against noise (bit and phase flip), security of quantum one-time pad and equivalence of quantum walks. © 2020 Copyright held by the owner/author(s).

关键词： Application programs computer circuits Couplings Verification Non trivial One time pads Post quantum securities Program logic Quantum programming Quantum teleportation Quantum walk Relational properties

来源：评论

学校读者我要写书评

暂无评论

Transformers in medical image analysis

引用

Intelligent Medicine 2023年第1期3卷 59-78页

作者： Kelei He Chen Gan Zhuoyuan Li Islem Rekik Zihao Yin Wen Ji Yang Gao Qian Wang Junfeng Zhang Dinggang Shen Medical School of Nanjing University NanjingJiangsu 210093China National Institute of Healthcare Data Science at Nanjing University NanjingJiangsu 210093China BASIRA Laboratory Faculty of Computer and Informatics EngineeringIstanbul Technical UniversityIstanbulTurkey School of Science and Engineering ComputingUniversity of DundeeUK State Key Laboratory for Novel Software Technology Nanjing UniversityNanjingJiangsu 210093China School of Biomedical Engineering ShanghaiTech UniversityShanghai 201210China Department of Research and Development Shanghai United Imaging Intelligence Co.Ltd.Shanghai 200030China Shanghai Clinical Research and Trial Center Shanghai 201703China

Transformers have dominated the field of natural language processing and have recently made an impact in the area of computer *** the field of medical image analysis,transformers have also been successfully used in to full-stack clinical applications,including image synthesis/reconstruction,registration,segmentation,detection,and *** paper aimed to promote awareness of the applications of transformers in medical image ***,we first provided an overview of the core concepts of the attention mechanism built into transformers and other basic ***,we reviewed various transformer architectures tailored for medical image applications and discuss their *** this review,we investigated key challenges including the use of transformers in different learning paradigms,improving model efficiency,and coupling with other *** hope this review would provide a comprehensive picture of transformers to readers with an interest in medical image analysis.

关键词： Transformer Medical image analysis Deep learning Diagnosis Registration Segmentation Image synthesis Multi-task learning Multi-modal learning Weakly-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Optimization for Multi-UAV-assisted Mobile Edge Computing

arXiv

引用

arXiv 2024年

作者： Sun, Geng Wang, Yixian Sun, Zemin Wu, Qingqing Kang, Jiawen Niyato, Dusit Leung, Victor C.M. College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China School of Automation Guangdong University of Technology Guangzhou510006 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

Recent developments in unmanned aerial vehicles (UAVs) and mobile edge computing (MEC) have provided users with flexible and resilient computing services. However, meeting the computing-intensive and latency-sensitive demands of users poses a significant challenge due to the limited resources of UAVs. To address this challenge, we present a multi-objective optimization approach for multi-UAV-assisted MEC systems. First, we formulate a multi-objective optimization problem aiming at minimizing the total task completion delay, reducing the total UAV energy consumption, and maximizing the total amount of offloaded tasks by jointly optimizing task offloading, computation resource allocation, and UAV trajectory control. Since the problem is a mixed-integer non-linear programming (MINLP) and NP-hard problem which is challenging, we propose a joint task offloading, computation resource allocation, and UAV trajectory control (JTORATC) approach to solve the problem. However, since the decision variables of task offloading, computation resource allocation, and UAV trajectory control are coupled with each other, the original problem is split into three sub-problems, i.e., task offloading, computation resource allocation, and UAV trajectory control, which are solved individually to obtain the corresponding decisions. Moreover, the sub-problem of task offloading is solved by using distributed splitting and threshold rounding methods, the sub-problem of computation resource allocation is solved by adopting the Karush-Kuhn-Tucker (KKT) method, and the sub-problem of UAV trajectory control is solved by employing the successive convex approximation (SCA) method. Simulation results show that the proposed JTORATC has superior performance compared to the other benchmark methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Patch-Based Data Management for Dual-Copy Buffers in RAID-Enabled SSDs

Patch-Based Data Management for Dual-Copy Buffers in RAID-En...

引用

作者： Li, Jun Sha, Zhibing Cai, Zhigang Trahay, Francois Liao, Jianwei College of Computer and Information Science Southwest University of China Chongqing China Computer Science Department Telecom SudParis Evry-Courcouronnes France State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

While a dual-copy redundant array of independent disk (RAID) buffering can remove single point of failure in the buffer of RAID-enabled solid-state drives (SSDs), it loses a half of buffer space efficiency as a result. This article introduces a patch-based data management scheme for dual-copy buffers in RAID-enabled SSDs, for better improving buffer use efficiency. Different from conventional methods that caches data/parity chunks in the RAID buffer, it caches the modified portions of data chunks (called data patches) and then employs a cost-evaluation model to direct patch data replacement. Besides, in order to correctly respond to applications' read/write requests, we design the patch-based read/write mode by taking the original dirty data chunks and relevant up-to-date patches into account. Through a series of simulation tests on several realistic disk traces, we illustrate that patch-based data management can work for RAID-enabled SSDs to enhance buffer use efficiency, and then yield better I/O performance. Especially, our proposal can noticeably reduce the I/O latency by 39.1% and the number of block erases by 3.9% on average, in contrast to state-of-the-art approaches. © 1982-2012 IEEE.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

A Low-Code Development Platform for Industrialized Insect-based Bioconversion Systems

A Low-Code Development Platform for Industrialized Insect-ba...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Cheng Pang Jinxian Liang Guangtao Yu Jibin Zhang Hiroaki Nishi Kevin I-Kai Wang Zeyuan Li Wenbin Dai Valeriy Vyatkin INSPRO Science Ltd. Shenzhen China Shenzhen Cynovan Technologies Co. Ltd. Shenzhen China National Key Laboratory of Agricultural Microbiology Huazhong Agricultural University Wuhan China Graduate School of Science and Technology Keio University Tokyo Japan Department of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand Googol Technology Co. Ltd. Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Computer Science Electrical and Space Engineering Luleå Tekniska Universitet Luleå Sweden

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Industrialized insect-based bioconversion is a technologically promising and economical viable approach for solving global crisis of food security and waste management. The successful implementation of such a multi-disciplinary system requires comprehensive expertise and skills from biotechnology, automation, information, and circular economy domains. This is rather difficult for existing practitioners. To simplify their jobs, by leveraging recent advances in industrial informatics, this work proposed and developed a low-code development platform for engineering the automation logic of industrial insect rearing and processing. For feasibility demonstration, a pilot facility has been designed, deployed, and benchmarked in this work. When compared with the conventional pro-code practice, the proposed low-code approach can significantly reduce development costs, shorten delivery times, and improve communication efficiency.

关键词： Waste management Industrial electronics Biotechnology Automation Costs Insects Food security

来源：评论

学校读者我要写书评

暂无评论

Neuromodulated Meta-Learning

arXiv

引用

arXiv 2024年

作者： Wang, Jingyao Guo, Huijie Qiang, Wenwen Li, Jiangmeng Zheng, Changwen Xiong, Hui Hua, Gang University of Chinese Academy of Sciences Beijing China National Key Laboratory of Space Integrated Information System Institute of Software Chinese Academy of Sciences Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China Thrust of Artificial Intelligence Hong Kong University of Science and Technology Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Wormpex AI Research LLC BellevueWA98004 United States

Humans excel at adapting perceptions and actions to diverse environments, enabling efficient interaction with the external world. This adaptive capability relies on the biological nervous system (BNS), which activates different brain regions for distinct tasks. Meta-learning similarly trains machines to handle multiple tasks but relies on a fixed network structure, not as flexible as BNS. To investigate the role of flexible network structure (FNS) in meta-learning, we conduct extensive empirical and theoretical analyses, finding that model performance is tied to structure, with no universally optimal pattern across tasks. This reveals the crucial role of FNS in meta-learning, ensuring meta-learning to generate the optimal structure for each task, thereby maximizing the performance and learning efficiency of meta-learning. Motivated by this insight, we propose to define, measure, and model FNS in meta-learning. First, we define that an effective FNS should possess frugality, plasticity, and sensitivity. Then, to quantify FNS in practice, we present three measurements for these properties, collectively forming the structure constraint with theoretical supports. Building on this, we finally propose Neuromodulated Meta-Learning (NeuronML) to model FNS in meta-learning. It utilizes bi-level optimization to update both weights and structure with the structure constraint. Extensive theoretical and empirical evaluations demonstrate the effectiveness of NeuronML on various tasks. Code is publicly available at https://***/WangJingyao07/NeuronML. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Self-Ensembling Semi-Supervised Model for Bone X-ray Images Landmark Detection

Self-Ensembling Semi-Supervised Model for Bone X-ray Images ...

引用

2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Bai, Tian Liu, Shenyao Wang, Yuzhao Wang, Yu Dong, Dong Jilin University College of Computer Science and Technology Changchun China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China College of Software Jilin University Changchun China Department of Radiology First Hospital of Jilin University Changchun China

ISBN: (纸本)9781665401265

Bone image landmark detection plays a vital role in orthopedic diseases diagnosis and analysis. As a promising approach, the data-driven convolutional neural network has been widely applied in landmarks detection. However, the model's performance relies heavily on numerous high-quality labeled data, which are difficult to access. A practical solution for this issue in bone images landmark detection has not been provided, so we propose a framework of semi-supervised bone images landmark detection encouraged by the recent success of the self-ensembling method. The student and teacher networks share the same structure in our framework, where unlabeled data are utilized by enforcing the prediction consistency of two networks under different perturbations to enhance the network's performance. The two networks use a mutual learning approach to improve the efficiency of using unlabeled data. In addition, we also propose a transformative perturbation scheme to prevent model overfitting during training and enhance the generalization capability of the model on unseen data. Experimental results on an in-house hip dataset collected from the actual process of clinical diagnosis and a publicly available dataset demonstrate that our framework has excellent performance compared with other semi-supervised methods. © 2021 IEEE.

关键词： Convolutional neural networks

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：