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Annual Conference on Neural Information Processing systems

作者： Yang Song Jun Zhu Yong Ren Dept. of Physics Tsinghua University Beijing China Dept. of Comp. Sci. & Tech. TNList LabCenter for Bio-Inspired Computing Research State Key Lab for Intell. Tech. & Systems Tsinghua University Beijing China

ISBN: (纸本)9781510838819

We propose a vector-valued regression problem whose solution is equivalent to the reproducing kernel Hilbert space (RKHS) embedding of the Bayesian posterior distribution. This equivalence provides a new understanding of kernel Bayesian inference. Moreover, the optimization problem induces a new regularization for the posterior embedding estimator, which is faster and has comparable performance to the squared regularization in kernel Bayes' rule. This regularization coincides with a former thresholding approach used in kernel POMDPs whose consistency remains to be established. Our theoretical work solves this open problem and provides consistency analysis in regression settings. Based on our optimizational formulation, we propose a flexible Bayesian posterior regularization framework which for the first time enables us to put regularization at the distribution level. We apply this method to nonparametric state-space filtering tasks with extremely nonlinear dynamics and show performance gains over all other baselines.

关键词： Bayesian inference Seeds Kernel embedding consistency Consistency (Measurement)

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Stochastic Gradient Geodesic MCMC Methods 16

Stochastic Gradient Geodesic MCMC Methods

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Annual Conference on Neural Information Processing systems

作者： Chang Liu Jun Zhu Yang Song Dept. of Comp. Sci. & Tech. TNList LabCenter for Bio-Inspired Computing Research State Key Lab for Intell. Tech. & Systems Tsinghua University Beijing China Dept. of Physics Tsinghua University Beijing China

ISBN: (纸本)9781510838819

We propose two stochastic gradient MCMC methods for sampling from Bayesian posterior distributions defined on Riemann manifolds with a known geodesic flow, e.g. hyperspheres. Our methods are the first scalable sampling methods on these manifolds, with the aid of stochastic gradients. Novel dynamics are conceived and 2nd-order integrators are developed. By adopting embedding tech.iques and the geodesic integrator, the methods do not require a global coordinate system of the manifold and do not involve inner iterations. Synthetic experiments show the validity of the method, and its application to the challenging inference for spherical topic models indicate practical usability and efficiency.

关键词： Coordinate system Manifolds Markov chain monte carlo methods Geodesic Riemann space Stochastic Posterior distribution integrators Automatic incident detection Sampling

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Why Did You Opt to Switch off Me? Big Data For Green Software Defined Networking

Why Did You Opt to Switch off Me? Big Data For Green Softwar...

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IEEE Globecom Workshops

作者： Chao Qiu Chenglin Zhao Haipeng Yao Fangmin Xu F. Richard Yu Key Lab. of Universal Wireless Comm. Ministry of Education Beijing University of Posts and Telecom. State Key Lab. of Networking and Switching Tech. Beijing Univ. of Posts and Telecom. Depart. of Systems and Computer Eng. Carleton Univ.

ISBN: (纸本)9781509024834

The pull of Software Defined Networking (SDN) which promises the formidable configuration, vigorous evolution and satisfactory performance is appealing. However, SDN is still in its initial period. Many issues remain to be delved and the most intractable one is the scalability of control plane with the explosive increase of network scales. In order to address this issue, splendid researches have presented multiple controllers to implement logically centralized control layer. Whilst, with the growing number of controllers, another hot potato emerges, which is the energy consumption. In our previous research, we proposed multiple controllers sleeping management which reduces the energy but introduces more delay. In this paper, based on the previous research, we propose the energy saving solution based on big data analysis. We utilize big data to analyse topology data in the system and excavate influence of each controller according to the analytic results. On this basis, the system opts to switch off controllers with smaller influence so as to reduce delay. Simulation results reveal that the improved method with big data analysis achieves superior time delay compared with the previous one.

关键词： green SDN big data energy consumption sleeping management

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Deco: False data detection and correction framework for participatory sensing

Deco: False data detection and correction framework for part...

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International Workshop on Quality of Service

作者： Long Cheng Linghe Kong Chengwen Luo Jianwei Niu Yu Gu Wenbo He Sajal Das State Key Lab of Networking & Switching Tech. Beijing Univ. of Posts & Telecomm. Beijing China State Key Lab of Virtual Reality Technology and Systems Beihang University Beijing China McGill University Canada National University of Singapore Singapore IBM Research Austin USA Missouri University of Science and Technology USA

Participatory sensing enables to collect a vast amount of data from the crowd by allowing a wide variety of sources to contribute data. However, the openness of participatory sensing exposes the system to malicious and erroneous participations, inevitably resulting in poor data quality. This brings forth the important issues of false data detection and correction in participatory sensing. Furthermore, data collected by participants normally include considerable missing values, which poses challenges for accurate false data detection. In this work, we propose DECO, a general framework to detect false values for participatory sensing in the presence of missing data. By applying a tailored spatio-temporal compressive sensing tech.ique, DECO is able to accurately detect the false data and estimate both false and missing values for data correction. We validate our design through an experimental case study.

关键词： Sensors Quality of service IEEE 802.11 Standard Atmospheric measurements Particle measurements Compressed sensing Estimation

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A Flight-Test Information Reasoning System Combining Textual CBR and RBR Approaches

A Flight-Test Information Reasoning System Combining Textual...

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7th International Conference on intelligent systems and Knowledge Engineering, ISKE 2012

作者： Yang, Bo Wang, Guodong Yao, Wentao State Key Laboratory of Intelligent Technology and Systems Tsinghua National Lab. for Information Science and Technology Dep. of Computer Science and Tech. Tsinghua University 100084 Beijing China Shenyang Aircraft Design and Research Institute 110031 Shenyang China

This paper presents a reasoning method based on the combination of Textual CBR and RBR to deal with the case described by the natural language with the intention of resolving the information retrieval in the flight-test procedure. Then experiments are made by using the reasoning system based on the method. The results show that not only could the method retrieve the cases from the system correctly, but also the Textual CBR procedure could complement the RBR procedure when the latter one cannot retrieve the case correctly. Thus the method could efficiently increase availability of the reasoning system. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Case based reasoning

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Programmable Supra‐Assembly of a DNA Surface Adapter for Tunable Chiral Directional Self‐Assembly of Gold Nanorods

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Angewandte Chemie 2017年第46期129卷

作者： Xiang Lan Zhaoming Su Yadong Zhou Travis Meyer Yonggang Ke Qiangbin Wang Wah Chiu Na Liu Shengli Zou Hao Yan Yan Liu Center for Molecular Design and Biomimetics The Biodesign Institute Arizona State University Tempe AZ 85287 USA School of Molecular Sciences Arizona State University Tempe AZ 85287 USA National Center for Macromolecular Imaging Verna and Marrs McLean Department of Biochemistry and Molecular Biology Baylor College of Medicine Houston TX 77030 USA Chemistry Department University of Central Florida 4111 Libra Drive Orlando FL 32816-2366 USA Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University 1760 Haygood Drive Health Sciences Research Bldg E186 Atlanta GA 30322 USA CAS Key Laboratory of Nano-Bio Interface Division of Nanobiomedicine and i-Lab Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Suzhou 215123 China Max Planck Institute for Intelligent Systems Heisenbergstrasse 3 70569 Stuttgart Germany Kirchhoff Institute for Physics University of Heidelberg Im Neuenheimer Feld 227 69120 Heidelberg Germany

An important challenge in molecular assembly and hierarchical molecular engineering is to control and program the directional self‐assembly into chiral structures. Here, we present a versatile DNA surface adapter that can programmably self‐assemble into various chiral supramolecular architectures, thereby regulating the chiral directional “bonding” of gold nanorods decorated by the surface adapter. Distinct optical chirality relevant to the ensemble conformation is demonstrated from the assembled novel stair‐like and coil‐like gold nanorod chiral metastructures, which is strongly affected by the spatial arrangement of neighboring nanorod pair. Our strategy provides new avenues for fabrication of tunable optical metamaterials by manipulating the directional self‐assembly of nanoparticles using programmable surface adapters.

关键词： Chiroptische Aktivität DNA-Selbstorganisation Gerichtete Selbstorganisation Nanopartikel Plasmonik

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Customized organization of social media contents using focused topic hierarchy 14

Customized organization of social media contents using focus...

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23rd ACM International Conference on Information and Knowledge Management, CIKM 2014

作者： Zhu, Xingwei Ming, Zhao-Yan Hao, Yu Zhu, Xiaoyan Chua, Tat-Seng State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Sci. and Tech. Tsinghua University China Department of Computer Science School of Computing National University of Singapore Singapore Singapore

ISBN: (纸本)9781450325981

With the popularity of social media platforms such as Face-book and Twitter, the amount of useful data in these sources is rapidly increasing, making them promising places for information acquisition. This research aims at the customized organization of a social media corpus using focused topic hierarchy. It organizes the contents into different structures to meet with users' different information needs (e.g., "iPhone 5 problem" or "iPhone 5 camera"). To this end, we introduce a novel function to measure the likelihood of a topic hierarchy, by which the users' information need can be incorporated into the process of topic hierarchy construction. Using the structure information within the generated topic hierarchy, we then develop a probability based model to identify the representative contents for topics to assist users in document retrieval on the hierarchy. Experimental results on real world data illustrate the effectiveness of our method and its superiority over state-of-the-art methods for both information organization and retrieval tasks. Copyright 2014 ACM.

关键词： Social networking (online)

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A neural reordering model for phrase-based translation 25

A neural reordering model for phrase-based translation

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25th International Conference on Computational Linguistics, COLING 2014

作者： Li, Peng Liu, Yang Sun, Maosong Izuha, Tatsuya Zhang, Dakun Department of Computer Sci. and Tech. State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Toshiba Corporation Corporate Research and Development Center Japan R and D Center China

ISBN: (纸本)9781941643266

While lexicalized reordering models have been widely used in phrase-based translation systems, they suffer from three drawbacks: context insensitivity, ambiguity, and sparsity. We propose a neural reordering model that conditions reordering probabilities on the words of both the current and previous phrase pairs. Including the words of previous phrase pairs significantly improves context sensitivity and reduces reordering ambiguity. To alleviate the data sparsity problem, we build one classifier for all phrase pairs, which are represented as continuous space vectors. Experiments on the NIST Chinese-English datasets show that our neural reordering model achieves significant improvements over state-of-the-art lexicalized reordering models.

关键词： Vector spaces

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Query lattice for translation retrieval 25

Query lattice for translation retrieval

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25th International Conference on Computational Linguistics, COLING 2014

作者： Dong, Meiping Cheng, Yong Liu, Yang Xu, Jia Sun, Maosong Izuha, Tatsuya Hao, Jie Department of Computer Sci. and Tech. State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Institute for Interdisciplinary Information Sciences Tsinghua University Beijing China Toshiba Corporation Corporate Research and Development Center Japan R and D Center China

ISBN: (纸本)9781941643266

Translation retrieval aims to find the most likely translation among a set of target-language strings for a given source-language string. Previous studies consider the single-best translation as a query for information retrieval, which may result in translation error propagation. To alleviate this problem, we propose to use the query lattice, which is a compact representation of exponentially many queries containing translation alternatives. We verified the effectiveness of query lattice through experiments, where our method explores a much larger search space (from 1 query to 1.24 × 1062 queries), runs much faster (from 0.75 to 0.13 second per sentence), and retrieves more accurately (from 83.76% to 93.16% in precision) than the standard method based on the query single-best. In addition, we show that query lattice significantly outperforms the method of (Munteanu and Marcu, 2005) on the task of parallel sentence mining from comparable corpora.

关键词： Translation (languages)

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The 5th International Conference on Biomedical Engineering and Biotech.ology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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