检索结果-内蒙古大学图书馆

arXiv 2019年

作者： Xu, Qianqian Sun, Xinwei Yang, Zhiyong Cao, Xiaochun Huang, Qingming Yao, Yuan Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Microsoft Research Asia State Key Laboratory of Information Security Institute of Information Engineering CAS School of Cyber Security University of Chinese Academy of Sciences School of Computer Science and Tech. University of Chinese Academy of Sciences Key Laboratory of Big Data Mining and Knowledge Management CAS Peng Cheng Laboratory Department of Mathematics Hong Kong University of Science and Technology Hong Kong

Due to the inherent uncertainty of data, the problem of predicting partial ranking from pairwise comparison data with ties has attracted increasing interest in recent years. However, in real-world scenarios, different individuals often hold distinct preferences. It might be misleading to merely look at a global partial ranking while ignoring personal diversity. In this paper, instead of learning a global ranking which is agreed with the consensus, we pursue the tie-aware partial ranking from an individualized perspective. Particularly, we formulate a unified framework which not only can be used for individualized partial ranking prediction, but also be helpful for abnormal user selection. This is realized by a variable splitting-based algorithm called iSplitLBI. Specifically, our algorithm generates a sequence of estimations with a regularization path, where both the hyperparameters and model parameters are updated. At each step of the path, the parameters can be decomposed into three orthogonal parts, namely, abnormal signals, personalized signals and random noise. The abnormal signals can serve the purpose of abnormal user selection, while the abnormal signals and personalized signals together are mainly responsible for individual partial ranking prediction. Extensive experiments on simulated and real-world datasets demonstrate that our new approach significantly outperforms state-of-the-art alternatives. The code is now availiable at https://***/qianqianxu010/ NeurIPS2019-iSplitLBI. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

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Adaptive Structure-Constrained Robust Latent Low-Rank Coding for Image Recovery

Adaptive Structure-Constrained Robust Latent Low-Rank Coding...

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IEEE International Conference on data Mining (ICDM)

作者： Zhao Zhang Lei Wang Sheng Li Yang Wang Zheng Zhang Zhengjun Zha Meng Wang School of Computer Science and Technology Soochow University Suzhou China Key Laboratory of Knowledge Engineering with Big Data (Ministry of Education) Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Computer Science University of Georgia Athens GA Bio-Computing Research Center Harbin Institute of Technology (Shenzhen) Shenzhen China School of Information Science and Technology University of Science and Technology of China Hefei China

In this paper, we propose a robust representation learning model called Adaptive Structure-constrained Low-Rank Coding (AS-LRC) for the latent representation of data. To recover the underlying subspaces more accurately, AS-LRC seamlessly integrates an adaptive weighting based block-diagonal structure-constrained low-rank representation and the group sparse salient feature extraction into a unified framework. Specifically, AS-LRC performs the latent decomposition of given data into a low-rank reconstruction by a block-diagonal codes matrix, a group sparse locality-adaptive salient feature part and a sparse error part. To enforce the block-diagonal structures adaptive to different real datasets for the low-rank recovery, AS-LRC clearly computes an auto-weighting matrix based on the locality-adaptive features and multiplies by the low-rank coefficients for direct minimization at the same time. This encourages the codes to be block-diagonal and can avoid the tricky issue of choosing optimal neighborhood size or kernel width for the weight assignment, suffered in most local geometrical structures-preserving low-rank coding methods. In addition, our AS-LRC selects the L2, 1-norm on the projection for extracting group sparse features rather than learning low-rank features by Nuclear-norm regularization, which can make learnt features robust to noise and outliers in samples, and can also make the feature coding process efficient. Extensive visualizations and numerical results demonstrate the effectiveness of our AS-LRC for image representation and recovery.

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QUANTUM LOVÁSZ LOCAL LEMMA: SHEARER’S BOUND IS TIGHT

arXiv

引用

arXiv 2018年

作者： He, Kun Li, Qian Sun, Xiaoming Zhang, Jiapeng The Key Lab of Data Engineering and Knowledge Engineering MOE Renmin University of China Beijing China Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China University of Southern California United States

The Lovász Local Lemma (LLL) is a very powerful tool in combinatorics and probability theory to show the possibility of avoiding all bad events under some weakly dependent conditions. In a seminal paper, Ambainis, Kempe, and Sattath (JACM 2012) introduced a quantum version LLL (QLLL) which shows the possibility of avoiding all "bad" Hamiltonians under some weakly dependent condition, and applied QLLL to the random k-QSAT problem. Sattath, Morampudi, Laumann, and Moessner (PNAS 2015) extended Ambainis, Kempe, and Sattath’s result and showed that Shearer’s bound is a sufficient condition for QLLL, and conjectured that Shearer’s bound is indeed the tight condition for QLLL. In this paper, we affirm this conjecture. Precisely, we prove that Shearer’s bound is tight for QLLL, i.e., the relative dimension of the smallest satisfying subspace is completely characterized by the independent set polynomial. Our result implies the tightness of Gilyén and Sattath’s algorithm (FOCS 2017), and also implies that the lattice gas partition function fully characterizes quantum satisfiability for almost all Hamiltonians with large enough qudits (Sattath, Morampudi, Laumann and Moessner, PNAS 2015). The commuting LLL (CLLL), which focuses on commuting local Hamiltonians, is also investigated here. We prove that the tight regions of CLLL and QLLL are different in general. This result indicates that it is possible to design an algorithm for CLLL which is still efficient beyond Shearer’s bound. Copyright © 2018, The Authors. All rights reserved.

关键词： Hamiltonians

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Heterogeneous-length text topic modeling for reader-Aware multi-document summarization

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ACM Transactions on knowledge Discovery from data 2019年第4期13卷 42-42页

作者： Qiang, Jipeng Chen, Ping Ding, Wei Wang, Tong Xie, Fei Wu, Xindong Department of Computer Science Yangzhou University China Department of Computer Science University of Massachusetts Boston United States Department of Computer Science and Technology Hefei Normal University China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei China Mininglamp Academy of Sciences Minininglamp Beijing 100084 China

More and more user comments like Tweets are available, which often contain user concerns. In order to meet the demands of users, a good summary generating from multiple documents should consider reader interests as reflected in reader comments. In this article, we focus on how to generate a summary from multi-document documents by considering reader comments, named as reader-Aware multi-document summarization (RA-MDS).We present an innovative topic-based method for RA-MDA, which exploits latent topics to obtain the most salient and lessen redundancy summary from multiple documents. Since finding latent topics for RA-MDS is a crucial step, we also present a Heterogeneous-length Text Topic Modeling (HTTM) to extract topics from the corpus that includes both news reports and user comments, denoted as heterogeneous-length texts. In this case, the latent topics extract by HTTM cover not only important aspects of the event, but also aspects that attract reader interests. Comparisons on summary benchmark datasets also confirm that the proposed RA-MDS method is effective in improving the quality of extracted summaries. In addition, experimental results demonstrate that the proposed topic modeling method outperforms existing topic modeling algorithms. © 2019 Association for Computing Machinery. All rights reserved.

关键词： heterogeneous-length text LDA multi-document summarization Topic modeling

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NaCdSb: An Orthorhombic Zintl Phase with Exceptional Intrinsic Thermoelectric Performance

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Angewandte Chemie 2022年第3期135卷

作者： Kai Guo Yuting Zhang Song Yuan Qinghang Tang Chen Lin Pengfei Luo Jiong Yang Shusheng Pan Li-Dong Zhao Guofeng Cheng Jiye Zhang Jun Luo School of Physics and Materials Science Guangzhou University Guangzhou 510006 China Research Center for Advanced Information Materials (CAIM) Huangpu Research & Graduate School of Guangzhou University Sino-Singapore Guangzhou Knowledge City Huangpu District Guangzhou 510555 China Contribution: Conceptualization (lead) Formal analysis (equal) Writing - original draft (lead) School of Materials Science and Engineering Shanghai University 99 Shangda Road Shanghai 200444 China Contribution: Data curation (equal) Investigation (equal) Validation (lead) Contribution: Data curation (lead) Formal analysis (equal) Materials Genome Institute Shanghai University 99 Shangda Road Shanghai 200444 China Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology Wuhan University Wuhan 430072 China Contribution: Investigation (equal) Contribution: Investigation (equal) Methodology (supporting) Contribution: Investigation (equal) Writing - review & editing (supporting) School of Materials Science and Engineering Beihang University Beijing 100191 China Contribution: Methodology (equal) Writing - review & editing (equal) Analysis & Testing Center for Inorganic Materials Shanghai Institute of Ceramics Chinese Academy of Sciences Shanghai 200050 China Contribution: Formal analysis (equal) Investigation (supporting) Contribution: Data curation (equal) Writing - review & editing (supporting) Contribution: Supervision (lead) Writing - review & editing (equal)

Many Zintl phases are promising thermoelectric materials owning to their features like narrow band gaps, multiband behaviors, ideal charge transport tunnels, and loosely bound cations. Herein we show a new Zintl phase NaCdSb with exceptional intrinsic thermoelectric performance. Pristine NaCdSb exhibits semiconductor behaviors with an experimental hole concentration of 2.9×10 18 cm −3 and a calculated band gap of 0.5 eV. As the temperature increases, the hole concentration rises gradually and approaches its optimal one, leading to a high power factor of 11.56 μW cm −1 K −2 at 673 K. The ultralow thermal conductivity is derived from the small phonon group velocity and short phonon lifetime, ascribed to the structural anharmonicity of Cd−Sb bonds. As a consequence, a maximum zT of 1.3 at 673 K has been achieved without any doping optimization or structural modification, demonstrating that NaCdSb is a remarkable thermoelectric compound with great potential for performance improvement.

关键词： Electron-Crystal NaCdSb Phonon-Glass Thermoelectric Properties Zintl Phase

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Research on the motivation to contribution and influencing factors of university students——a semi-structured interview based on qualitative research

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IOP Conference Series: Materials Science and engineering 2019年第5期563卷

作者： Yueyao Li Sanhong Deng Yue Zhang School of Information Management Nanjing University Nanjing 210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing 210023 China

Due to the lack of theoretical knowledge and practical experience, the university students have many deficiencies in contribution. We conducted semi-structured interviews with 28 undergraduate and postgraduate students of Nanjing Agricultural University. At the same time, we used descriptive statistics and cross-analysis methods to analyse the motivations of college students' initial contribution and the influencing factor of their choice. Based on this, this paper puts forward some suggestions for the initial submission of college students, and the journals are also provided for reference in the selection of manuscripts.

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Research on Influencing Factors of College Students' Intention of Online Health Information Behavior Based on Social Cognitive Theory

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Journal of Physics: Conference Series 2019年第2期1213卷

作者： Jia Kong Sanhong Deng Yue Zhang School of Information Management Nanjing University Nanjing 210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing 210023 China

Based on the Social Cognition Theory, we constructed the influencing factors model of college students' intention of online health information behavior from three levels of individual, society and information systems, which was analyzed by using the PLS-SEM. Research shows that self-efficacy, information service quality, social support, information literacy and information quality significantly influence college students' intention of online health information behavior. However, the influence of perceived risk and information system quality is not significant.

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Corrigendum to: Multi-Swarm Cuckoo Search Algorithm withQ-Learning Model

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The Computer Journal 2022年第7期65卷 1938-1938页

作者： Li, Juan Xiao, Dan-dan Zhang, Ting Liu, Chun Li, Yuan-xiang Wang, Gai-ge School of Artificial Intelligence Wuhan Technology and Business University Wuhan 430065 China School of Artificial Intelligence Wuchang University of Technology Wuhan 430223 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University No. 2699 Qianjin Street Gaoxin District Changchun Jilin China 130012 School of Computer Wuhan University No. 299 Bayi Street Wuchang District Wuhan Hubei China 430072 Department of Computer Science and Technology Ocean University of China No. 238 Songling Street Laoshan District Qingdao Shandong China 266100 Institute of Algorithm and Big Data Analysis Northeast Normal University No. 5268 Renmin Street Nanguan District Changchun Jilin China 130117

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Do we measure novelty when we analyze unusual combinations of cited references? A validation study of bibliometric novelty indicators based on F1000Prime data

arXiv

引用

arXiv 2019年

作者： Bornmann, Lutz Tekles, Alexander Zhang, Helena H. Ye, Fred Y. Division for Science and Innovation Studies Administrative Headquarters of the Max Planck Society Hofgartenstr. 8 Munich80539 Germany Ludwig-Maximilians-Universität Munich Department of Sociology Konradstr. 6 Munich80801 Germany Jiangsu Key Laboratory of Data Engineering Knowledge Service School of Information Management Nanjing University Nanjing210023 China Nanjing University Nanjing China University of Illinois Champaign United States

Lee, Walsh, and Wang (2015) – based on Uzzi, Mukherjee, Stringer, and Jones (2013) – and Wang, Veugelers, and Stephan (2017) proposed scores based on cited references (cited journals) data which can be used to measure the novelty of papers (named as novelty scores U and W in this study). Although previous research has used novelty scores in various empirical analyses, no study has been published up to now – to the best of our knowledge – which quantitatively tested the convergent validity of novelty scores: do these scores measure what they propose to measure? Using novelty assessments by faculty members (FMs) at F1000Prime for comparison, we tested the convergent validity of the two novelty scores (U and W). FMs’ assessments not only refer to the quality of biomedical papers, but also to their characteristics (by assigning certain tags to the papers): for example, are the presented findings or formulated hypotheses novel (tags "new findings" and "hypothesis")? We used these and other tags to investigate the convergent validity of both novelty scores. Our study reveals different results for the novelty scores: the results for novelty score U are mostly in agreement with previously formulated expectations. We found, for instance, that for a standard deviation (one unit) increase in novelty score U, the expected number of assignments of the "new finding" tag increase by 7.47%. The results for novelty score W, however, do not reflect convergent validity with the FMs’ assessments: only the results for some tags are in agreement with the expectations. Thus, we propose – based on our results – the use of novelty score U for measuring novelty quantitatively, but question the use of novelty score W. Copyright © 2019, The Authors. All rights reserved.

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Structure formation dynamics in drawing silica photonic crystal fibres

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Frontiers of Optoelectronics 2018年第1期11卷 69-76页

作者： Wenyu WANG Ghazal Fallah TAFTI Mingjie DING Yanhua LUO Yuan TIAN Shuai WANG Tomasz KARPISZ John CANNING Kevin COOK Gang-Ding PENG Photonics and Optical Communications School of Electrical Engineering and Telecommunications University of New South Wales (UNSW) Sydney 2052 Australia Henan Key Laboratory of Laser and Opto-Electric Information Technology School of Information Engineering Zhengzhou University Zhengzhou 450052 China Warsaw University of Technology 00-665 Warsaw Poland interdisciplinary Photonics Laboratories (iPL) School of Electrical and Data EngineeringUniversity of Technology Sydney and School of Chemistry The University of Sydney NSW 2007 & 2006 Australia

The special features of photonic crystal fibres（PCFs）are achieved by their air hole *** structure is determined and formed by its origin preform design and drawing ***,structure formation dynamics in drawing PCF is important for the fabrication of PCF achieving desirable structure and thus the intended *** paper will investigate structure formation dynamics of PCF drawing in relation to key parameters and conditions,such as hole dimension,temperature,pressure,etc.

关键词： photonic crystal fibre （PCF） structure formation hole dimension hole position hole shift

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