检索结果-内蒙古大学图书馆

Landscape of global urban environmental resistome and its association with local socioeconomic and medical status

science China(Life sciences) 2024年第6期67卷 1292-1301页

作者： Jun Wu Yige Hu Michael H Perlin David Danko Jun Lu Manuela Oliveira Johannes Werner Maria M Zambrano Maria A Sierra Olayinka O Osuolale Paweł Łabaj Nicolás Rascovan Nur Hazlin Hazrin-Chong Soojin Jang Haruo Suzuki Marina Nieto-Caballero Bharath Prithiviraj Patrick K H Lee Agnieszka Chmielarczyk Anna Różańska Yongxiang Zhao Lan Wang Christopher E Mason Tieliu Shi Center for Bioinformatics and Computational Biology and the Institute of Biomedical SciencesSchool of Life SciencesEast China Normal UniversityShanghai 200241China Department of Biology Program on Disease EvolutionUniversity of LouisvilleLouisville 40292USA Weill Cornell Medicine New York 10065USA The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine New York 10065USA Department of Pulmonary Medicine Shanghai Chest HospitalShanghai Jiao Tong UniversityShanghai 200025China i3S-Instituto de Investiga玢o e Inova玢o em Saúde Universidade do PortoPorto 4050-290Portugal Ipatimup-Instituto de Patologia e Imunologia Molecular da Universidade do Porto Porto 4200-465Portugal Departamento de Biologia Faculdade de CiênciasUniversidade do PortoPorto 4050-290Portugal High Performance and Cloud Computing Group Zentrum für Datenverarbeitung(ZDV)Eberhard Karls University of TübingenW鋍hterstra遝7672074TübingenGermany Corporación Corpogen Research Center Bogotá110311Colombia Applied Environmental Metagenomics and Infectious Diseases Research(AEMIDR) Department of Biological SciencesElizade UniversityIlara-Mokin 340271Nigeria Maopolska Centre of Biotechnology Jagiellonian UniversityKraków 30-005Poland Aix-Marseille Université Mediterranean Institute of OceanologyUniversitéde ToulonCNRSIRDUM 110Marseille 83041France Department of Biological Sciences and Biotechnology Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangor Institut Pasteur Korea Seoul 13488Republic of Korea Faculty of Environment and Information Studies Keio UniversityFujisawaKanagawa 252-0882Japan University of Colorado at Boulder CivilEnvironmental and Architectural DepartmentBoulder 80303USA Brooklyn College of the City University of New York Brooklyn 11210USA School of Energy and Environment City University of Hong KongHong Kong 999077China Department of Microbiology Faculty of MedicineJagiellonian UniversityKraków 30-005Poland Biological Targeting Diagnosis and The

Antimicrobial resistance(AMR)poses a critical threat to global health and development,with environmental factors—particularly in urban areas—contributing significantly to the spread of antibiotic resistance genes(ARGs).However,most research to date has been conducted at a local level,leaving significant gaps in our understanding of the global status of antibiotic resistance in urban *** address this issue,we thoroughly analyzed a total of 86,213 ARGs detected within 4,728 metagenome samples,which were collected by the Meta SUB International Consortium involving diverse urban environments in 60 cities of 27 countries,utilizing a deep-learning based *** findings demonstrated the strong geographical specificity of urban environmental resistome,and their correlation with various local socioeconomic and medical *** also identified distinctive evolutionary patterns of ARG-related biosynthetic gene clusters(BGCs)across different countries,and discovered that the urban environment represents a rich source of novel *** study provides a comprehensive overview of the global urban environmental resistome,and fills a significant gap in our knowledge of large-scale urban antibiotic resistome analysis.

关键词： urban environment metagenome antibiotic resistance resistance diversity biosynthetic gene clusters

来源：评论

学校读者我要写书评

暂无评论

Reliable Collaborative Semi-infrastructure Vehicle-to-Vehicle Communication for Local File Sharing 15th

Reliable Collaborative Semi-infrastructure Vehicle-to-Vehicl...

引用

15th EAI International Conference on Collaborative computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Mokhtar, Bassem Azab, Mohamed Fathalla, Efat Ghourab, Esraa M. Magdy, Mohamed Eltoweissy, Mohamed Electrical Engineering Department Alexandria University Alexandria Egypt Computer Engineering Program School of Engineering and Applied Sciences Nile University Giza Egypt Computer and Information Sciences Virginia Military Institute LexingtonVA24450 United States Department of Electrical and Computer Engineering Old Dominion University NorfolkVA United States College of Computing and Information Technology Arab Academy for Science Technology and Maritime Transport Alexandria Egypt

ISBN: (纸本)9783030301453

Recently, Vehicular Cloud Communication (VCC) has been gaining momentum targeting intelligent and efficient data transmission. VCC is a type of mobile ad-hoc network comprising heterogeneous vehicles sharing their resources to perform collaborative activities. In this paper, we propose a new semi-infrastructure file-browsing in order to provide Network as a service (NaaS) enabling internet-independent browsing. In our scenario, a central management platform plays the role of controlling and managing the selection of relaying vehicles supporting the source to destination file transmission procedure. Nagel-Schreckenberg rules for traffic cellular automata (CA) are used as the basis for our scenario simulation. Nagel-Schreckenberg rules simulate the behavior of a group of hypothetical vehicles moving across a highway. We study the reliability and efficiency of file transfer in such settings. Simulation results show that the number of selected relays required to establish the network highly impacts the probability of successfully sending the requested files. In addition, the distances between the selected relays influence the network throughput and the probability of network failure. Moreover, the density of relays strongly affects the overall delay that occurs due to the continuous re-transmission of the selected files among different hops. © 2019, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Vehicle to vehicle communications

来源：评论

学校读者我要写书评

暂无评论

Efficient Breast Cancer Diagnosis from Complex Mammographic Images Using Deep Convolutional Neural Network

引用

Computational intelligence and neuroscience 2023年第1期2023卷 7717712页

作者： Hameedur Rahman Tanvir Fatima Naik Bukht Rozilawati Ahmad Ahmad Almadhor Abdul Rehman Javed Department of Computer Games Development Faculty of Computing and AI Air University E9 Islamabad Pakistan. Department of Computer Science Faculty of Computing and AI Air University E9 Islamabad Pakistan. Diagnostic Imaging and Radiotherapy Program Therapeutic and Investigation Studies Faculty of Health Sciences University Kebangsaan Malaysia Kuala Lumpur Malaysia. Department of Computer Engineering and Networks College of Computer and Information Sciences Jouf University Sakaka 72388 Saudi Arabia. Department of Cyber Security Air University Islamabad Pakistan. Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon.

Medical image analysis places a significant focus on breast cancer, which poses a significant threat to women's health and contributes to many fatalities. An early and precise diagnosis of breast cancer through digital mammograms can significantly improve the accuracy of disease detection. Computer-aided diagnosis (CAD) systems must analyze the medical imagery and perform detection, segmentation, and classification processes to assist radiologists with accurately detecting breast lesions. However, early-stage mammography cancer detection is certainly difficult. The deep convolutional neural network has demonstrated exceptional results and is considered a highly effective tool in the field. This study proposes a computational framework for diagnosing breast cancer using a ResNet-50 convolutional neural network to classify mammogram images. To train and classify the INbreast dataset into benign or malignant categories, the framework utilizes transfer learning from the pretrained ResNet-50 CNN on ImageNet. The results revealed that the proposed framework achieved an outstanding classification accuracy of 93%, surpassing other models trained on the same dataset. This novel approach facilitates early diagnosis and classification of malignant and benign breast cancer, potentially saving lives and resources. These outcomes highlight that deep convolutional neural network algorithms can be trained to achieve highly accurate results in various mammograms, along with the capacity to enhance medical tools by reducing the error rate in screening mammograms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Airr Community Curation and Standardised Representation for Immunoglobulin and T Cell Receptor Germline Sets

SSRN

引用

SSRN 2022年

作者： Lees, William D. Christley, Scott Peres, Ayelet Kos, Justin T. Corrie, Brian Ralph, Duncan Breden, Felix Cowell, Lindsay G. Yaari, Gur Corcoran, Martin Karlsson Hedestam, Gunilla B. Ohlin, Mats Collins, Andrew M. Watson, Corey T. Busse, Christian E. Institute of Structural and Molecular Biology Birkbeck College London United Kingdom Human-Centered Computing and Information Science Institute for Systems and Computer Engineering Technology and Science Porto Portugal Peter O’Donnell Jr School of Public Health Department of Immunology UT Southwestern Medical Center Texas United States Bioengineering Program Faculty of Engineering Bar-Ilan University Ramat Gan Israel Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville Kentucky United States Department of Biological Sciences Simon Fraser University BurnabyBC Canada Fred Hutchinson Cancer Research Center SeattleWA United States Department of Microbiology Tumor and Cell Biology Karolinska Institute Stockholm Sweden Department of Immunotechnology Lund University Lund Sweden School of Biotechnology and Biomolecular Sciences University of New South Wales SydneyNSW Australia Division of B Cell Immunology German Cancer Research Center Heidelberg Germany

Analysis of an individual’s immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes and provides transparency based on principles of findability, accessibility, interoperability, and reusability. We describe results obtained by applying the data model and associated principles within the AIRR Community, including supporting software and databases. © 2022, The Authors. All rights reserved.

关键词： Genes

来源：评论

学校读者我要写书评

暂无评论

Comparative Study of Masking and Mapping Based on Hierarchical Extreme Learning Machine for Speech Enhancement

Comparative Study of Masking and Mapping Based on Hierarchic...

引用

IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Ryandhimas E. Zezario Join W. C. Sigalingging Tassadaq Hussain Jia-Ching Wang Yu Tsao Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan National Central University Taoyuan Taiwan Taiwan International Graduate Program in Social Network and Human-Centered Computing Institute of Information Science Academia Sinica Taipei Taiwan

In this study, we compare the speech enhancement performance based on hierarchical extreme learning machine (HELM) with two distinct strategies: masking and mapping. Experimental results of the perceptual evaluation of speech quality (PESQ) show that for both of limited and sufficient amounts of training data, mapping-based HELM tends to be more effective to improve the performance of speech enhancement.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Intelligent E-commerce for Special Needs

Intelligent E-commerce for Special Needs

引用

International Conference on Cyber and IT Service Management (CITSM)

作者： Diana Teresia Spits Warnars Leonardo Primadala Putra Logiansa Harco Leslie Hendric Spits Warnars Wiranto Herry Utomo School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computing President University Bekasi Indonesia

Special need is a person who need assistance for their disabilities which include medical, physical, mental or psychological such as person with autism, down syndrome, dyslexia, Attention Deficit Hyperactivity Disorder (ADHD), multiple sclerosis, schizophrenia, cystic fibrosis, cerebral palsy, muscular dystrophy, blindness, deafness, epilepsy, chronic asthma and so on. In this proposed research idea about intelligent E-commerce for special needs, we limited to four types of difficulties such as hearing difficulty, vision difficulty, language difficulty, and learning difficulty. In this paper, we interest in those special needs persons who can use e-commerce and how to model a system that can help them to joy and easy to join with e-commerce. For some, this intelligent e-commerce is not only for shopping only but will become part of their healing for special needs in order to engage with daily human activities and increase their daily confidence in life. This paper also a preliminary investigation that can be used for Ph.D. or Doctoral research degree who is interested in building e-commerce framework for people with a special need or disability.

关键词： Companies Machine learning Speech recognition Tools Pricing

来源：评论

学校读者我要写书评

暂无评论

Harmonized-Multinational qEEG norms (HarMNqEEG)

引用

NEUROIMAGE 2022年 256卷 119190-119190页

作者： Li, Min Wang, Ying Lopez-Naranjo, Carlos Hu, Shiang Reyes, Ronaldo Cesar Garcia Paz-Linares, Deirel Areces-Gonzalez, Ariosky Hamid, Aini Ismafairus Abd Evans, Alan C. Savostyanov, Alexander N. Calzada-Reyes, Ana Villringer, Arno Tobon-Quintero, Carlos A. Garcia-Agustin, Daysi Yao, Dezhong Dong, Li Aubert-Vazquez, Eduardo Reza, Faruque Razzaq, Fuleah Abdul Omar, Hazim Abdullah, Jafri Malin Galler, Janina R. Ochoa-Gomez, John F. Prichep, Leslie S. Galan-Garcia, Lidice Morales-Chacon, Lilia Valdes-Sosa, Mitchell J. Trondle, Marius Zulkifly, Mohd Faizal Mohd Rahman, Muhammad Riddha Bin Abdul Milakhina, Natalya S. Langer, Nicolas Rudych, Pavel Koenig, Thomas Virues-Alba, Trinidad A. Lei, Xu Bringas-Vega, Maria L. Bosch-Bayard, Jorge F. Valdes-Sosa, Pedro Antonio [a]The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China [b]Cuban Center for Neurocience La Habana Cuba [c]McGill Centre for Integrative Neuroscience Ludmer Centre for Neuroinformatics and Mental Health Montreal Neurological Institute Canada [d]Department of Neurosciences School of Medical Sciences Universiti Sains Malaysia Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [e]Brain and Behaviour Cluster School of Medical Sciences Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [f]Hospital Universiti Sains Malaysia Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [g]Humanitarian Institute Novosibirsk State University Novosibirsk 630090 Russia [h]Laboratory of Psychophysiology of Individual Differences Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine Novosibirsk 630117 Russia [i]Laboratory of Psychological Genetics at the Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences Novosibirsk 630090 Russia [j]University of Pinar del Río “Hermanos Saiz Montes de Oca” Pinar del Río Cuba [k]Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany [l]Department of Cognitive Neurology University Hospital Leipzig Leipzig Germany [m]Center for Stroke Research Charité-Universitätsmedizin Berlin Berlin Germany [n]Grupo Neuropsicología y Conducta - GRUNECO Faculty of Medicine Universidad de Antioquia Colombia [o]Research Department Institución Prestadora de Servicios de Salud IPS Universitaria Colombia [p]The Cuban center aging longevity and health Havana Cuba [q]Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu 2019RU035 China [r]School of Electrical Engineering Zhengzhou University Zhengzhou 4500

This paper extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects " and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.

关键词： Quantitative EEG EEG cross-spectrum Riemannian geometry Batch effects Z-score Harmonization Malnutrition Covid induced brain dysfunction Developmental Brain Chart

来源：评论

学校读者我要写书评

暂无评论

Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

引用

The Lancet Digital Health 2025年第5期7卷 100868页

作者： Meng, Ziyao Guan, Zhouyu Yu, Shujie Wu, Yilan Zhao, Yaoning Shen, Jie Lim, Cynthia Ciwei Chen, Tingli Yang, Dawei Ran, An Ran He, Feng Hamzah, Haslina Singh, Sarkaaj Abd Raof, Anis Syazwani Lee-Boey, Jian Wen Samuel Lim, Soo-Kun Sun, Xufang Ge, Shuwang Xu, Gang Su, Hua Cheng, Yang Lu, Feng Liao, Xiaofei Jin, Hai Deng, Chenxin Ruan, Lei Zhang, Cuntai Wu, Chan Dai, Rongping Jin, Yixiao Wang, Wenxiao Li, Tingyao Liu, Ruhan Li, Jiajia Shu, Jia Lu, Yuwei Wang, Xiangning Wu, Qiang Qin, Yiming Tang, Jin Sheng, Xiaohua Jiao, Qiong Yang, Xiaokang Guo, Minyi McKay, Gareth J Hogg, Ruth E Liew, Gerald Chee, Evelyn Yi Lyn Hsu, Wynne Lee, Mong Li Szeto, Simon Luk, Andrea O Y Chan, Juliana C N Cheung, Carol Y Tan, Gavin Siew Wei Tham, Yih-Chung Cheng, Ching-Yu Sabanayagam, Charumathi Lim, Lee-Ling Jia, Weiping Li, Huating Sheng, Bin Wong, Tien Yin Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Institute for Proactive Healthcare Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Centre for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Beijing Tsinghua Changgung Hospital Eye Center School of Clinical Medicine Tsinghua Medicine Tsinghua University Beijing China Medical Records and Statistics Office Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Renal Medicine Singapore General Hospital SingHealth-Duke Academic Medical Centre Singapore Singapore Department of Ophthalmology Shanghai Health and Medical Center Wuxi China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong Special Administrative Region China Singapore Eye Research Institute Singapore National Eye Centre Singapore Department of Medicine Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia Department of Ophthalmology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Hubei Wuhan China Department of Nephrology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Nephrology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Ophthalmology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Centre for Big Dat

Background: Improving the accessibility of screening diabetic kidney disease (DKD) and differentiating isolated diabetic nephropathy from non-diabetic kidney disease (NDKD) are two major challenges in the field of diabetes care. We aimed to develop and validate an artificial intelligence (AI) deep learning system to detect DKD and isolated diabetic nephropathy from retinal fundus images. Methods: In this population-based study, we developed a retinal image-based AI-deep learning system, DeepDKD, pretrained using 734 084 retinal fundus images. First, for DKD detection, we used 486 312 retinal images from 121 578 participants in the Shanghai Integrated Diabetes Prevention and Care System for development and internal validation, and ten multi-ethnic datasets from China, Singapore, Malaysia, Australia, and the UK (65 406 participants) for external validation. Second, to differentiate isolated diabetic nephropathy from NDKD, we used 1068 retinal images from 267 participants for development and internal validation, and three multi-ethnic datasets from China, Malaysia, and the UK (244 participants) for external validation. Finally, we conducted two proof-of-concept studies: a prospective real-world study with 3 months' follow-up to evaluate the effectiveness of DeepDKD in screening DKD;and a longitudinal analysis of the effectiveness of DeepDKD in differentiating isolated diabetic nephropathy from NDKD on renal function changes with 4·6 years' follow-up. Findings: For detecting DKD, DeepDKD achieved an area under the receiver operating characteristic curve (AUC) of 0·842 (95% CI 0·838–0·846) on the internal validation dataset and AUCs of 0·791–0·826 across external validation datasets. For differentiating isolated diabetic nephropathy from NDKD, DeepDKD achieved an AUC of 0·906 (0·825–0·966) on the internal validation dataset and AUCs of 0·733–0·844 across external validation datasets. In the prospective study, compared with the metadata model, DeepDKD could detect DKD wit

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Content-Based Echo Chamber Detection on Social Media Platforms

Content-Based Echo Chamber Detection on Social Media Platfor...

引用

International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Fernando H. Calderón Li-Kai Cheng Ming-Jen Lin Yen-Hao Huang Yi-Shin Chen Social Networks and Human Centered Computing Taiwan International Graduate Program Institute of Information Science Academia Sinica Hsinchu City Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu City Taiwan National Taiwan University Taipei City Taiwan

ISBN: (数字)9781450368681

ISBN: (纸本)9781450368681

“Echo chamber” is a metaphorical description of a situation in which beliefs are amplified inside a closed network, and social media platforms provide an environment that is well-suited to this phenomenon. Depending on the scale of the echo chamber, a user's judgment of different opinions may be restricted. The current study focuses on detecting echoing interaction between a post and its related comments to then quantify the predominating degree of echo chamber behavior on Facebook pages. To enable such detection, two content-based features are designed; the first aids stance representation of comments on a particular discussion topic, and the second focuses on the type and intensity of emotion elicited by a subject. This work also introduces data-driven semi-supervised approaches to extract such features from social media data.

关键词： Feature extraction Social network services Fans Urban areas Connectors Linguistics Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Quantum-inspired classical sublinear-time algorithm for solving low-rank semidefinite programming via sampling approaches

arXiv

引用

arXiv 2019年

作者： Chia, Nai-Hui Li, Tongyang Lin, Han-Hsuan Wang, Chunhao Department of Computer Science University of Texas Austin United States Department of Computer Science Institute for Advanced Computer Studies Joint Center for Quantum Information and Computer Science University of Maryland U.S. Department of Energy Office of Science Office of Advanced Scientific Computing Research Quantum Algorithms Teams program

Semidefinite programming (SDP) is a central topic in mathematical optimization with extensive studies on its efficient solvers. Recently, quantum algorithms with superpolynomial speedups for solving SDPs have been proposed assuming access to its constraint matrices in quantum superposition. Mutually inspired by both classical and quantum SDP solvers, in this paper we present a sublinear classical algorithm for solving low-rank SDPs which is asymptotically as good as existing quantum algorithms. Specifically, given an SDP with m constraint matrices, each of dimension n and rank poly(log n), our algorithm gives a succinct description and any entry of the solution matrix in time O(m · poly(log n, 1/Ε)) given access to a sample-based low-overhead data structure of the constraint matrices, where Ε is the precision of the solution. In addition, we apply our algorithm to a quantum state learning task as an application. Technically, our approach aligns with both the SDP solvers based on the matrix multiplicative weight (MMW) framework and the recent studies of quantum-inspired machine learning algorithms. The cost of solving SDPs by MMW mainly comes from the exponentiation of Hermitian matrices, and we propose two new technical ingredients (compared to previous sample-based algorithms) for this task that may be of independent interest: • Weighted sampling: assuming sampling access to each individual constraint matrix A1,..., Aτ, we propose a procedure that gives a good approximation of A = A1 + ··· + Aτ. • Symmetric approximation: we propose a sampling procedure that gives low-rank spectral decomposition of a Hermitian matrix A. This improves upon previous sampling procedures that only give low-rank singular value decompositions, losing the signs of eigenvalues. Copyright © 2019, The Authors. All rights reserved.

关键词： Singular value decomposition

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：