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检索条件"机构=Key Laboratory of Network Data Science and Technology Institute of Computing Technology"
6108 条 记 录,以下是4651-4660 订阅
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A theoretically guaranteed deep optimization framework for robust compressive sensing MRI
arXiv
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arXiv 2018年
作者: Liu, Risheng Zhang, Yuxi Cheng, Shichao Fan, Xin Luo, Zhongxuan DUT-RU International School of Information Science & Engineering Dalian University of Technology Dalian China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian China School of Mathematical Science Dalian University of Technology Dalian China Institute of Artificial Intelligence Guilin University of Electronic Technology Dalian
Magnetic Resonance Imaging (MRI) is one of the most dynamic and safe imaging techniques available for clinical applications. However, the rather slow speed of MRI acquisitions limits the patient throughput and potenti... 详细信息
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Observation of a New Excited Beauty Strange Baryon Decaying to Ξb−π+π−
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Physical Review Letters 2021年 第25期126卷 252003-252003页
作者: A. M. Sirunyan A. Tumasyan W. Adam J. W. Andrejkovic T. Bergauer S. Chatterjee M. Dragicevic A. Escalante Del Valle R. Frühwirth M. Jeitler N. Krammer L. Lechner D. Liko I. Mikulec F. M. Pitters J. Schieck R. Schöfbeck M. Spanring S. Templ W. Waltenberger C.-E. Wulz V. Chekhovsky A. Litomin V. Makarenko M. R. Darwish E. A. De Wolf X. Janssen T. Kello A. Lelek H. Rejeb Sfar P. Van Mechelen S. Van Putte N. Van Remortel F. Blekman E. S. Bols J. D’Hondt J. De Clercq M. Delcourt S. Lowette S. Moortgat A. Morton D. Müller A. R. Sahasransu S. Tavernier W. Van Doninck P. Van Mulders D. Beghin B. Bilin B. Clerbaux G. De Lentdecker L. Favart A. Grebenyuk A. K. Kalsi K. Lee M. Mahdavikhorrami I. Makarenko L. Moureaux L. Pétré A. Popov N. Postiau E. Starling L. Thomas M. Vanden Bemden C. Vander Velde P. Vanlaer D. Vannerom L. Wezenbeek T. Cornelis D. Dobur M. Gruchala L. Lambrecht G. Mestdach M. Niedziela C. Roskas K. Skovpen T. T. Tran M. Tytgat W. Verbeke B. Vermassen M. Vit A. Bethani G. Bruno F. Bury C. Caputo P. David C. Delaere I. S. Donertas A. Giammanco K. Jaffel V. Lemaitre K. Mondal J. Prisciandaro A. Taliercio M. Teklishyn P. Vischia S. Wertz S. Wuyckens G. A. Alves C. Hensel A. Moraes W. L. Aldá Júnior M. Barroso Ferreira Filho H. Brandao Malbouisson W. Carvalho J. Chinellato E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza D. Matos Figueiredo C. Mora Herrera K. Mota Amarilo L. Mundim H. Nogima P. Rebello Teles L. J. Sanchez Rosas A. Santoro S. M. Silva Do Amaral A. Sznajder M. Thiel F. Torres Da Silva De Araujo A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores D. S. Lemos P. G. Mercadante S. F. Novaes Sandra S. Padula A. Aleksandrov G. Antchev I. Atanasov R. Hadjiiska P. Iaydjiev M. Misheva M. Rodozov M. Shopova G. Sultanov A. Dimitrov T. Ivanov L. Litov B. Pavlov P. Petkov A. Petrov T. Cheng W. Fang Q. Guo T. Javaid M. Mittal H. Wang L. Yuan M. Ahmad G. Bauer C. Dozen Z. Hu J. Martins Y. Wang K. Yi E. Chapon G. M. Chen H. S. Chen M. Chen F. Iemmi A Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Korea University Seoul Korea Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista São Paulo Brazil Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China Rutgers The State University of New Jersey Piscataway New Jersey USA Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China Massachusetts Institute of Technology Cambridge Massachusetts USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China The University of Kansas Lawrence Kansas USA Sun Yat-Sen University Guangzhou China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE)—Fudan University Shanghai China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics (CHEP-FU) Fa
The Ξb−π+π− invariant mass spectrum is investigated with an event sample of proton-proton collisions at s=13 TeV, collected by the CMS experiment at the LHC in 2016–2018 and corresponding to an integrated luminos... 详细信息
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Gradient descent finds global minima of deep neural networks
arXiv
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arXiv 2018年
作者: Du, Simon S. Lee, Jason D. Li, Haochuan Wang, Liwei Zhai, Xiyu Machine Learning Department Carnegie Mellon University Data Science and Operations Department University of Southern California School of Physics Peking University Center for Data Science Peking University Beijing Institute of Big Data Research Key Laboratory of Machine Perception Moe School of Eecs Peking University Department of Eecs Massachusetts Institute of Technology
Gradient descent finds a global minimum in training deep neural networks despite the objective function being non-convex. The current paper proves gradient descent achieves zero training loss in polynomial time for a ... 详细信息
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Model inconsistent but correlated noise: Multi-view subspace learning with regularized Mixture of Gaussians
arXiv
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arXiv 2018年
作者: Yong, Hongwei Meng, Deyu Li, Jinxing Zuo, Wangmeng Zhang, Lei Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong School of Mathematics and Statistics Ministry of Education Key Lab of Intelligent Networks and Network Security Xian Jiaotong University School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China
Multi-view subspace learning (MSL) aims to find a low-dimensional subspace of the data obtained from multiple views. Different from single view case, MSL should take both common and specific knowledge among different ... 详细信息
来源: 评论
Graph convolutional neural networks via motif-based attention
arXiv
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arXiv 2018年
作者: Peng, Hao Li, Jianxin Gong, Qiran Wang, Senzhang Ning, Yuanxing Yu, Philip S. Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University State Key Laboratory of Software Development Environment Beihang University Collage of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Department of Computer Science University of Illinois at Chicago
Many real-world problems can be represented as graph-based learning problems. In this paper, we propose a novel framework for learning spatial and attentional convolution neural networks on arbitrary graphs. Different... 详细信息
来源: 评论
Constraints on Cosmic Strings Using data from the Third Advanced LIGO–Virgo Observing Run
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Physical Review Letters 2021年 第24期126卷 241102-241102页
作者: R. Abbott T. D. Abbott S. Abraham F. Acernese K. Ackley A. Adams C. Adams R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith T. Akutsu K. M. Aleman G. Allen A. Allocca P. A. Altin A. Amato S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando S. V. Angelova S. Ansoldi J. M. Antelis S. Antier S. Appert Koya Arai Koji Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud S. M. Aronson H. Asada Y. Asali G. Ashton Y. Aso S. M. Aston P. Astone F. Aubin P. Auclair P. Aufmuth K. AultONeal C. Austin S. Babak F. Badaracco M. K. M. Bader S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer M. Bals A. Balsamo G. Baltus S. Banagiri D. Bankar R. S. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo S. Barnum F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal M. G. Benjamin T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi D. Bersanetti A. Bertolini J. Betzwieser R. Bhandare A. V. Bhandari D. Bhattacharjee S. Bhaumik J. Bidler I. A. Bilenko G. Billingsley R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn J. Blackman C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant A. Buikema T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic L. Cadonati M. Caesar G. Cagnoli C. Cahillane H. W. Cain, III J. Calderón Bustillo J. D LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Inter-University Centre for Astronomy and Astrophysics Pune 411007 India Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S.Angelo I-80126 Napoli Italy OzGrav School of Physics and Astronomy Monash University Clayton 3800 Victoria Australia Christopher Newport University Newport News Virginia 23606 USA LIGO Livingston Observatory Livingston Louisiana 70754 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom Gran Sasso Science Institute (GSSI) I-67100 L’Aquila Italy INFN Laboratori Nazionali del Gran Sasso I-67100 Assergi Italy INFN Sezione di Pisa I-56127 Pisa Italy Università di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan California State University Fullerton Fullerton California 92831 USA NCSA University of Illi
We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as ... 详细信息
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Erratum to “High-Efficiency Min-Entropy Estimation Based on Neural network for Random Number Generators”
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Security and Communication networks 2020年 第1期2020卷
作者: Na Lv Tianyu Chen Shuangyi Zhu Jing Yang Yuan Ma Jiwu Jing Jingqiang Lin State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 *** Data Assurance and Communications Security Research Center Chinese Academy of Sciences Beijing 100093 *** School of Cyber Security University of Chinese Academy of Sciences Beijing 100093 *** China Information Technology Security Evaluation Center Beijing 100085 *** School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100093 ***
来源: 评论
Analysis of Influencing Factors on Carbon Monoxide Utilization Rate of Blast Furnace Based on Multi-Timescale Characteristics  36
Analysis of Influencing Factors on Carbon Monoxide Utilizati...
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第36届中国控制会议
作者: Jianqi An Yuwan Yang Min Wu Takao Terano School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Computer Science School of ComputingTokyo Institute of Technology
In the blast furnace,due to the different changing frequency of different operations,and the different reaction time of gas,liquid and solid materials,there exists multi-timescale characteristics in the iron-making **... 详细信息
来源: 评论
Jerk-Level Cyclic Motion Planning and Control for Constrained Redundant Robot Manipulators Using Zhang Dynamics:Theoretics
Jerk-Level Cyclic Motion Planning and Control for Constraine...
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第30届中国控制与决策会议
作者: Min Yang Yunong Zhang Huanchang Huang Dechao Chen Jian Li School of Information Science and Technology Sun Yat-sen University(SYSU) Key Laboratory of Autonomous Systems and Networked Control Ministry of Education SYSU-CMU Shunde International Joint Research Institute Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education
In this paper,based on Zhang dynamics method(ZDM),a cyclic motion planning(CMP) scheme is developed to remedy the joint drift phenomenon of redundant robot manipulators constrained by joint physical *** existing w... 详细信息
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Cubic medium field equation public key cryptosystem
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International Journal of network Security 2018年 第3期20卷 472-477页
作者: Lu, Gang Xue, Linyuan Nie, Xuyun Qin, Zhiguang Liu, Bo School of Information and Software Engineering University of Electronic Science and Technology of China 4 Jianshe North Rd 2nd Section Chenghua Qu Chengdu610054 China State Key Laboratory of Information Security Institute of Information Engineering Beijing100093 China Network and Data Security Key Laboratory of Sichuan Province Chengdu610054 China
Medium Field Equation (MFE) multivariate public key cryptosystems were broken by High Order Linearization Equation (HOLE) attack. In order to avoid HOLE attack, we proposed an improvement of MFE, Cubic MFE public key ... 详细信息
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