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The Journal of Machine Learning research 2020年第1期21卷 8590-8628页

作者： Fanghui Liu Xiaolin Huang Chen Gong Jie Yang Li Li Department of Electrical Engineering ESAT-STADIUS KU Leuven Belgium Institute of Image Processing and Pattern Recognition Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China PCA Lab Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology China and Department of Computing Hong Kong Polytechnic University Hong Kong SAR China Department of Automation BNRist Tsinghua University China

In this paper, we propose a data-adaptive non-parametric kernel learning framework in margin based kernel methods. In model formulation, given an initial kernel matrix, a data-adaptive matrix with two constraints is imposed in an entry-wise scheme. Learning this data-adaptive matrix in a formulation-free strategy enlarges the margin between classes and thus improves the model flexibility. The introduced two constraints are imposed either exactly (on small data sets) or approximately (on large data sets) in our model, which provides a controllable trade-off between model flexibility and complexity with theoretical demonstration. In algorithm optimization, the objective function of our learning framework is proven to be gradient-Lipschitz continuous. Thereby, kernel and classifier/regressor learning can be efficiently optimized in a unified framework via Nesterov's acceleration. For the scalability issue, we study a decomposition-based approach to our model in the large sample case. The effectiveness of this approximation is illustrated by both empirical studies and theoretical guarantees. Experimental results on various classification and regression benchmark data sets demonstrate that our non-parametric kernel learning framework achieves good performance when compared with other representative kernel learning based algorithms.

关键词： support vector machines non-parametric kernel learning gradient-Lipschitz continuous

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Geo-spatial ontology matching through compact evolutionary algorithm 2nd

Geo-spatial ontology matching through compact evolutionary a...

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2nd International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2018

作者： Xue, Xingsi Liu, Jianhua College of Information Science and Engineering Fujian University of Technology FuzhouFujian350118 China Intelligent Information Processing Research Center Fujian University of Technology FuzhouFujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology FuzhouFujian350118 China Fujian Key Lab for Automotive Electronics and Electric Drive Fujian University of Technology FuzhouFujian350118 China

ISBN: (纸本)9783030045845

Geo-spatial ontologies can provide a formal description of concepts, relationships, activities, features and rules in GIS domain. However, simply use them only allows to partially solve semantic conflicts, and does not completely solve heterogeneity issues that are caused by themselves. Geo-spatial ontology matching technique can find the correspondences between semantic identical entities, and solve the heterogeneous problem between two geo-spatial ontologies. Be inspired by the successful application of Evolutionary Algorithm (EA) in instance matching domain, in this paper, it is utilized to match the heterogeneous geo-spatial ontologies. To reduce the runtime and memory consumption required by EA, a compact version of it is presented, which does not work on the whole population but a probability representation on it. In addition, a geo-spatial similarity measure is presented to determine the identical geo-spatial entities, and an optimal model is constructed for geo-spatial ontology matching problem. The experimental results show that cEA-based geo-spatial ontology matching technique can efficiently determine the alignment. © Springer Nature Switzerland AG 2019.

关键词： Evolutionary algorithms

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Publisher Correction: Compact angle-resolved metasurface spectrometer

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Nature materials 2025年第4期24卷 650页

作者： Guiyi Cai Yanhao Li Yao Zhang Xiong Jiang Yimu Chen Geyang Qu Xudong Zhang Shumin Xiao Jiecai Han Shaohua Yu Yuri Kivshar Qinghai Song Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of Technology Shenzhen People's Republic of China. Pengcheng Laboratory Shenzhen People's Republic of China. Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of Technology Shenzhen People's Republic of China. shumin.xiao@***. Pengcheng Laboratory Shenzhen People's Republic of China. shumin.xiao@***. National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of Technology Harbin People's Republic of China. shumin.xiao@***. National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of Technology Harbin People's Republic of China. Pengcheng Laboratory Shenzhen People's Republic of China. yush@***. Nonlinear Physics Center Research School of Physics Australian National University Canberra Australian Capital Territory Australia. yuri.kivshar@anu.edu.au. Qingdao Innovation and Development Center Harbin Engineering University Qingdao People's Republic of China. yuri.kivshar@anu.edu.au. Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of Technology Shenzhen People's Republic of China. qinghai.song@***. Pengcheng Laboratory Shenzhen People's Republic of China. qinghai.song@***. Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan People's Republic of China. qinghai.song@***.

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RGB-T image saliency detection via collaborative graph learning

arXiv

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arXiv 2019年

作者： Tu, Zhengzheng Xia, Tian Li, Chenglong Wang, Xiaoxiao Ma, Yan Tang, Jin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Institute of Physical Science and Information Technology Anhui University Hefei China

Image saliency detection is an active research topic in the community of computer vision and multimedia. Fusing complementary RGB and thermal infrared data has been proven to be effective for image saliency detection. In this paper, we propose an effective approach for RGB-T image saliency detection. Our approach relies on a novel collaborative graph learning algorithm. In particular, we take superpixels as graph nodes, and collaboratively use hierarchical deep features to jointly learn graph affinity and node saliency in a unified optimization framework. Moreover, we contribute a more challenging dataset for the purpose of RGB-T image saliency detection, which contains 1000 spatially aligned RGB-T image pairs and their ground truth annotations. Extensive experiments on the public dataset and the newly created dataset suggest that the proposed approach performs favorably against the state-of-the-art RGB-T saliency detection methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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An insight into acupoints and meridians in human body based on interstitial fluid circulation

arXiv

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arXiv 2020年

作者： Li, Hongyi Yin, Yajun Hu, Jun Li, Hua Wang, Fang Ji, Fusui Ma, Chao Cardiology Department Beijing Hospital National Center of Gerontology Beijing China Department of Engineering Mechanics Tsinghua University Beijing China Key Lab of Interfacial Physics and Technology Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai China Shanghai Synchrotron Radiation Facility Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China Key Lab of Intelligent Information Processing Institute of Computing Technology University of Chinese Academy of Sciences Beijing China Institute of Basic Medical Sciences Chinese Academy of Medical Sciences Department of Human Anatomy Histology and Embryology School of Basic Medicine Peking Union Medical College Beijing China Chinese Institute for Brain Research Beijing China

The atlas of human acupoints and meridians has been utilized in clinical practice for almost a millennium although the anatomical structures and functions remain to be clarified. It has recently been reported that a long-distance interstitial fluid (ISF) circulatory pathway may originate from the acupoints in the extremities. As observed in living human subjects, cadavers and animals using magnetic resonance imaging and fluorescent tracers, the ISF flow pathways include at least 4 types of anatomical structures: the cutaneous-, perivenous-, periarterial-, and neural-pathways. Unlike the blood or lymphatic vessels, these ISF flow pathways are composed of highly ordered and topologically connected interstitial fibrous connective tissues that may work as guiderails for the ISF to flow actively over long distance under certain driving forces. Our experimental results demonstrated that most acupoints in the extremity endings connect with one or more ISF flow pathways and comprise a complex network of acupoint-ISF-pathways. We also found that this acupoint-ISF-pathway network can connect to visceral organs or tissues such as the pericardium and epicardium, even though the topographical geometry in human extremities does not totally match the meridian lines on the atlas that is currently used in traditional Chinese medicine. Based on our experimental data, the following working hypotheses are proposed: 1, there are one or more ISF flow pathways, including at least one cutaneous pathway, originated from an acupoint on the body surface. 2, the acupoints on the body surface specifically connect with certain visceral organs or tissues via ISF flow. And 3, the acupoint-originated ISF pathways constitute a complex connective network and can modulate the ISF and bio-signals in the microenvironments around cells in certain visceral organs or tissues from body surfaces. A comprehensive atlas will be constructed to systemically reveal the detailed anatomical structures of the acupoi

关键词： Histology

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(Bi_(0.51)Na_(0.47))TiO_(3) based lead free ceramics with high energy density and efficiency

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Journal of Materiomics 2019年第3期5卷 385-393页

作者： Yu Huang Fei Li Hua Hao Fangquan Xia Hanxing Liu Shujun Zhang State Key Lab Silicate Materials for Architecture Center for Smart Materials and Device IntegrationSchool of Materials Science and EngineeringWuhan University of TechnologyWuhan430070China Electronic Materials Research Laboratory Key Lab Ministry of Education and International Center for Dielectric ResearchSchool of Electronic and Information EngineeringXi'an Jiaotong UniversityXi'an710049China School of Chemistry and Chemical Engineering University of JinanJinan250022China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Smart Materials and Device IntegrationInternational School of Materials Science and EngineeringWuhan University of TechnologyWuhan430070China Institute for Superconducting and Electronic Materials Australian Institute of Innovative MaterialsUniversity of WollongongNSW2500Australia

Dielectric ceramics with high energy storage density and energy efficiency play an important role in high power energy storage *** this work,lead free relaxor ferroelectric ceramics in (1-x) Bi_(0.51)Na_(0.47)TiO_(3-x)Ba(Zr_(0.3)Ti_(0.7))O_(3)(BNT-BZT100x:x=0.20,0.30,0.40 and 0.50)system are fabricated by conventional solid-state sintering *** BNT-BZT100x ceramics are sintered dense with minimal pores,exhibiting pseudocubic symmetry and strong relaxor characteristic.A high energy storage density of 3.1 J/cm^(3) and high energy efficiency of 91% are simultaneously achieved in BNT-BZT40 ceramic with 0.1mm in thickness,at the applied electric field of 280 kV/*** temperature stability of the energy density is studied over temperature range of 20-160℃ ,showing minimal variation below 1.5%,together with the excellent cycling reliability(the variations of both energy density and efficiency are below 3% up to 106 cycles),making BNT-BZT40 ceramic promising candidate for high-temperature dielectric and energy storage applications.

关键词： Energy storage Lead free ceramic Relaxor characteristic

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Corrigendum to “Discovering and learning sensational episodes of news events” [Inf. Syst. 78 (2018) 68–80]

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information Systems 2020年 93卷

作者： Xiang Ao Ping Luo Chengkai Li Fuzhen Zhuang Qing He Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China University of Texas at Arlington USA

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Towards interpretable deep neural networks by leveraging adversarial examples

arXiv

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arXiv 2019年

作者： Dong, Yinpeng Bao, Fan Su, Hang Zhu, Jun Tsinghua National Lab for Information Science and Technology State Key Lab of Intelligent Technology and Systems Center for Bio-Inspired Computing Research Department of Computer Science and Technology Tsinghua University Beijing100084 China

Sometimes it is not enough for a DNN to produce an outcome. For example, in applications such as healthcare, users need to understand the rationale of the decisions. Therefore, it is imperative to develop algorithms to learn models with good interpretability (Doshi-Velez 2017). An important factor that leads to the lack of interpretability of DNNs is the ambiguity of neurons, where a neuron may fire for various unrelated concepts. This work aims to increase the interpretability of DNNs on the whole image space by reducing the ambiguity of neurons. In this paper, we make the following contributions: • We propose a metric to evaluate the consistency level of neurons in a network quantitatively. • We find that the learned features of neurons are ambiguous by leveraging adversarial examples. • We propose to improve the consistency of neurons on adversarial example subset by an adversarial training algorithm with a consistent loss. Copyright © 2019, The Authors. All rights reserved.

关键词： Neurons

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Identifying High Potential Talent: A Neural Network Based Dynamic Social Profiling Approach

Identifying High Potential Talent: A Neural Network Based Dy...

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IEEE International Conference on Data Mining (ICDM)

作者： Yuyang Ye Hengshu Zhu Tong Xu Fuzhen Zhuang Runlong Yu Hui Xiong Anhui Province Key Lab of Big Data Analysis and Application University of Science and Technology of China Baidu Talent Intelligence Center Baidu Inc Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology University of Chinese Academy of Sciences

How to identify high-potential talent (HIPO) earlier in their career always has strategic importance for human resource management. While tremendous efforts have been made in this direction, most existing approaches are still based on the subjective selection of human resource experts. This could lead to unintentional bias and inconsistencies. To this end, in this paper, we propose a neural network based dynamic social profiling approach for quantitatively identifying HIPOs from the newly-enrolled employees by modeling the dynamics of their behaviors in organizational social networks. A basic assumption is that HIPOs usually perform more actively and have higher competencies than their peers to accumulate their social capitals during their daily work practice. Along this line, we first propose to model the social profiles of employees with both Graph Convolutional Network (GCN) and social centrality analysis in a comprehensive way. Then, an adaptive Long Short Term Memory (LSTM) network with global attention mechanism is designed to capture the profile dynamics of employees in the organizational social networks during their early career. Finally, extensive experiments on real-world data clearly validate the effectiveness of our approach as well as the interpretability of our results.

关键词： Social networking (online) Companies Artificial neural networks Germanium Engineering profession

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Mapping disulfide bonds from sub-micrograms of purified proteins or micrograms of complex protein mixtures

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Biophysics Reports 2018年第2期4卷 68-81页

作者： Shan Lu Yong Cao Sheng-Bo Fan Zhen-Lin Chen Run-Qian Fang Si-Min He Meng-Qiu Dong National Institute of Biological Sciences Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) University of CAS Institute of Computing Technology CAS University of Chinese Academy of Sciences

Disulfide bonds are vital for protein functions, but locating the linkage sites has been a challenge in protein chemistry, especially when the quantity of a sample is small or the complexity is high. In 2015,our laboratory developed a sensitive and efficient method for mapping protein disulfide bonds from simple or complex samples(Lu et al. in Nat Methods 12:329, 2015). This method is based on liquid chromatography–mass spectrometry(LC–MS) and a powerful data analysis software tool named p *** facilitate application of this method, we present step-by-step disulfide mapping protocols for three types of samples—purified proteins in solution, proteins in SDS-PAGE gels, and complex protein mixtures in solution. The minimum amount of protein required for this method can be as low as several hundred nanograms for purified proteins, or tens of micrograms for a mixture of hundreds of *** entire workflow—from sample preparation to LC–MS and data analysis—is described in great detail. We believe that this protocol can be easily implemented in any laboratory with access to a fastscanning, high-resolution, and accurate-mass LC–MS system.

关键词： Cross-linking Disulfide Identification of disulfide bonds Mass spectrometry PLink PLink-SS

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