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Annual Conference on Neural information Processing systems

作者： Pinghua Gong Jieping Ye Changshui Zhang State Key Laboratory on Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology (TNList) Department of Automation Tsinghua University Beijing 100084 China Computer Science and Engineering Center for Evolutionary Medicine and Informatics The Biodesign Institute Arizona State University Tempe AZ 85287 USA

ISBN: (纸本)9781627480031

Multi-task sparse feature learning aims to improve the generalization performance by exploiting the shared features among tasks. It has been successfully applied to many applications including computer vision and biomedical informatics. Most of the existing multi-task sparse feature learning algorithms are formulated as a convex sparse regularization problem, which is usually suboptimal, due to its looseness for approximating an ?_0o-type regularizer. In this paper, we propose a non-convex formulation for multi-task sparse feature learning based on a novel regularizer. To solve the non-convex optimization problem, we propose a Multistage Multi-Task Feature Learning (MSMTFL) algorithm. Moreover, we present a detailed theoretical analysis showing that MSMTFL achieves a better parameter estimation error bound than the convex formulation. Empirical studies on both synthetic and real-world data sets demonstrate the effectiveness of MSMTFL in comparison with the state of the art multi-task sparse feature learning algorithms.

关键词： Learning learning algorithms Non-Convex Biomedical informatics Theoretical analysis Parameter estimation images computer vision state of the art Dataset Convexity Religious Missions SYNTHETICS

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Doubly selective channel estimation for amplify-and-forward relay networks

Doubly selective channel estimation for amplify-and-forward ...

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IEEE Conference on Wireless Communications and Networking

作者： Gongpu Wang Feifei Gao Jiaru Lin Chintha Tellambura School of Computer and Information Technology Beijing Jiaotong University China National Mobile Communications Research Laboratory South East University Nanjing China State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing China Key Laboratory of Universal Wireless Communications Ministry of Education China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

In this paper, the estimation of doubly selective channel is considered for amplify-and-forward (AF) relay networks. The complex exponential basis expansion model (CE-BEM) is chosen to describe the time-varying channel, from which the infinite channel parameters are mapped onto finite ones. Since direct estimation of these coefficients encounters high computational complexity and large spectral cost, we develop an efficient estimator targeting at some specially defined channel parameters. The training sequence design that can minimize the channel estimation mean-square error is also proposed.

关键词： Training Channel estimation Relays Wireless communication Educational institutions Estimation Vectors

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Strategic Robust Mixed Model Assembly Line Balancing Based on Scenario Planning

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Tsinghua science and Technology 2011年第3期16卷 308-314页

作者：徐炜达肖田元 National Laboratory for Information Science and Technology National Computer Integrated Manufacturing Systems Engineering Research CenterDepartment of AutomationTsinghua University

Assembly line balancing involves assigning a series of task elements to uniform sequential stations with certain restrictions. Decision makers often discover that a task assignment which is optimal with respect to a deterministic or stochastic/fuzzy model yields quite poor performance in reality. In real environments, assembly line balancing robustness is a more appropriate decision selection guide. A robust model based on the α worst case scenario is developed to compensate for the drawbacks of traditional robust criteria. A robust genetic algorithm is used to solve the problem. Comprehensive computational experiments to study the effect of the solution procedure show that the model generates more flexible robust solutions. Careful tuning the value of α allows the decision maker to balance robustness and conservativeness of as- sembly line task element assignments.

关键词： mixed model assembly line balancing robust scenario planning genetic algorithm

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The hot topics evaluation and key issues in online news about emergency events

The hot topics evaluation and key issues in online news abou...

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World Congress on Intelligent Control and automation (WCICA)

作者： Liping Chen Junping Du Katsunori Shimohara Maoqiang Song Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer Science Beijing University of Posts and Telecommunications Beijing China Department of Information Systems Design Doshisha University Kyotanabe Kyoto Japan Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing University of Posts and Telecommunications Beijing China

This paper concentrates on the evaluation system of hot topics in the online news about the emergency events. First, the overall technology framework of the system was established and description was formulated on the key issues need to be resolved prior to the evaluation of the hot topics. Focusing on the vector representation of the news documents and clustering algorithm of the news topics, a modified TF-IDF text representation model was formulated and an improved selection method of initial topic clustering center was established. The evaluation model of the hot topics was then established to evaluate the heat value of the clustered topics based on extracting websites feature parameters, such as the time properties of the news reports, reporting properties, and user attention. Finally, the paper takes news of 2011 Japan Earthquake as data source for algorism and model evaluation. The results showed that the identification and evaluation system of hot topics in online news about the emergency events was valid, and the evaluation result of hot topics by the systems agreed with the expected results. It lays a foundation for the subsequent studying about the tracking and evolution of the hot topics.

关键词： Vectors Heating Feature extraction Media Educational institutions Earthquakes Time frequency analysis

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Fuzzy H∞ filtering for nonlinear singularly perturbed systems with time-varying delay

Fuzzy H∞ filtering for nonlinear singularly perturbed syste...

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2011 8th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Li, Yaping Chen, Jinxiang Meng, Lixia He, Meiyun Beijing Information Technology College Beijing 100015 China State Key Laboratory of Hybrid Process Industry Automation System and Equipment Technology Automation Research and Design Institute of Metallurgical Industry 100071 China Department of Computer Science and Technology Tsinghua University Army Aviation College Beijing 100084 China Department of Mechanism Army Aviation College Beijing 100123 China

ISBN: (纸本)9781612841816

This paper investigates the problem of designing fuzzy H∞ filter for a class of nonlinear singularly perturbed systems (SPSs) with time-varying delay in states. The considered system is approximated by a Takagi-Sugeno (T-S) fuzzy model. By using linear matrix inequality (LMI) methods, we give a -independent sufficient condition for the existence of fuzzy H∞ filter such that, the resulting filtering error system is globally stable with guaranteed H∞ performance for sufficiently small . The gains of filter are obtained by solving a set of -independent LMIs, and therefore the ill-conditioned problem caused by can be easily avoid. The proposed method can be applied to both standard and nonstandard nonlinear SPSs. A numerical example is provided to illustrate the effectiveness of the developed method. © 2011 IEEE.

关键词： Perturbation techniques

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A conceptual framework for semantic case-based safety analysis

A conceptual framework for semantic case-based safety analys...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Olawande Daramola Tor Stålhane Thomas Moser Stefan Biffl Department of Computer and Information Science Norwegian University of Science and Technology Norway Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems Vienna University of Technology Austria

Hazard and Operability (HAZOP) Analysis and Failure Mode and Effect Analysis (FMEA) are among the most widely used safety analysis procedures in the development of safety-critical and embedded systems. These analyses are generally perceived as complex and time-consuming, hindering an effective reuse of previous results or experiences. In this paper we present a conceptual semantic case-based framework for safety analysis, which facilitates the reuse of previous HAZOP and FMEA experiences in order to reduce the time and effort associated with these analyses. We present the core technologies of the conceptual framework and evaluated a prototype of the framework, KROSA, in an experiment with domain experts at ABB Norway. Initial results confirm the viability of the conceptual framework for industrial application.

关键词： Ontologies Semantics Natural language processing Libraries Hazards Humans

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Analysis of a Partially Decentralized Framework for Operating Future Power systems

Analysis of a Partially Decentralized Framework for Operatin...

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IEEE Power and Energy Society General Meeting

作者： Mingyang Li Peter B. Luh Eugene Litvinov Peng Zhang Center for Intelligent and Networked Systems (CFINS) Department of Automation Tsinghua National Laboratory for Information Science & Technology (TNLIST) Tsinghua University Dept. of Electrical & Computer Engineering University of Connecticut ISO New England Inc.

ISBN: (纸本)9781457710001

In future power systems, the Smart Grid technologies will bring in a large number of new entities, which are different from those in the current systems in two major aspects: first, the entities are geographically distributed throughout the system with their detailed information not available to the system operator, and second, the entities tend to autonomously optimize their own benefits. In view of both aspects, it is difficult to use the current centralized framework to operate future systems. In this paper, we present and analyze a new partially decentralized framework and the corresponding mechanisms as one step from the current framework toward the future ones, and the focus is on the real time electricity markets with a dispatch cycle of five minutes. In each dispatch cycle, the system operator posts electricity price forecasts, and individual entities actively respond to the prices to dispatch themselves. The system-wide power imbalance is used as a correction term in the next dispatch cycle to iteratively update the price forecasts, so that system balance is maintained in the long term. The new framework can accommodate the large number of entities without knowing their detailed information, and enable the entities to achieve better economic benefits. Small examples are used to analyze our framework and to compare it with the current one.

关键词： System operation Autonomous entities Renewable generation Decentralized Real time market Electricity price Decentralized Operating systems Dispatching Electricity pricing Frameworks power systems correct entry Smart grids Prices

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A swarm intelligence based searching strategy for articulated 3D human body tracking

A swarm intelligence based searching strategy for articulate...

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2010 IEEE computer Society Conference on computer Vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Zhang, Xiaoqin Hu, Weiming Wang, Xiangyang Kong, Yu Xie, Nianhua Wang, Hanzi Ling, Haibin Maybank, Steve College of Mathematics and Information Science Wenzhou University Zhejiang China National Laboratory of Pattern Recognition Institute of Automation Beijing China School of Communication and Information Engineering Shanghai University Shanghai China School of Computer Science Beijing Institute of Technology Beijing China School of Computer Science University of Adelaide Australia Department of Computer and Information Science Temple University Philadelphia United States School of Computer Science and Information Systems Birkbeck College London United Kingdom

ISBN: (纸本)9781424470297

This paper proposes an annealed particle swarm optimization based particle filter algorithm for articulated 3D human body tracking. In our algorithm, a sampling covariance and an annealing factor are incorporated into the velocity updating equation of particle swarm optimization (PSO). The sampling covariance and the annealing factor are initiated with appropriate values at the beginning of the PSO iteration, and 'annealing' is carried out at reasonable steps. Experiments with multi-camera walking sequences from the Brown dataset show that: 1) the proposed tracker can effectively alleviate the problem of inconsistency between the image likelihood and the true model;2) the tracker is also robust to noise and body self-occlusion. © 2010 IEEE.

关键词： Swarm intelligence

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Reducing stick-slip motion in one-dimensional nano manipulation by real-time feedback control

Reducing stick-slip motion in one-dimensional nano manipulat...

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2010 10th IEEE Conference on Nanotechnology, NANO 2010

作者： Zhang, Jing Miao, Lei Wu, Re-Bing Xi, Ning Li, Chun-Wen Wang, Yue-Chao Tarn, Tzyh-Jong Department of Automation Tsinghua University Beijing 100084 China Center for Quantum Information Science and Technology Tsinghua National Laboratory for Information Science and Technology Beijing 100084 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Beijing 110016 China Department of Electrical and Computer Engineering Michigan State University East Lansing MI 48824 United States Department of Electrical and Systems Engineering Washington University St. Louis MO 63130 United States

ISBN: (纸本)9781424470334

When a micro cantilever with a nanoscale tip is manipulated on a substrate with atomic roughness, e.g., pushing an atomic-scale sample or etching the surface of the substrate to draw desired patterns, the periodical lateral frictional forces with stochastic fluctuations will induce stick-slip motion of the cantilever tip, which may greatly influence the precision of the nano manipulation. To reduce such a stick-slip motion, we propose a feedback control strategy based on the position estimation of the cantilever tip to compensate the periodical frictional force. Numerical simulations show that the motion of the cantilever tip under feedback control can track the desired trajectory asymptotically. Our proposal can aL be extended to the case when the cantilever tip moves over a Gaussian-shape defection on the substrate and when the stochastic fluctuations in the lateral force are with non-zero correlation time. ©2010 IEEE.

关键词： Feedback control

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Evolutionary Self-learning Scheduling Approach for Wireless Sensor Network

Evolutionary Self-learning Scheduling Approach for Wireless ...

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2010 International Conference on Intelligent Computation Technology and automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

作者： Jianjun Niu State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China Beijing Special Engineering Design and Resear

Energy efficiency is very important for wireless sensor network (WSN). This paper presents an evolutionary self-learning scheduling approach (ESSA) to reduce energy consumption for WSN. The ESSA is based on a new proposed scheme - evolutionary Q-learning with continuousaction (EQC) approach, which combines an extension of Q-learning method with particle swarm optimization (PSO) algorithm. The action space of EQC is partitioned into lots of subintervals. And each endpoint of the subintervals is characterized by a discrete action value and a Q-value. The continuous action value is the weighted average of discrete actions according to their Q values. The PSO algorithm is combined to let an agent profit the experience of other agents. We valid the ESSA in a MAC protocol and simulation results show that the ESSA is an effective method and performs much better than SMAC protocol.

关键词： Wirless Sensor Network Scheduling Q-Learning Particle Swarm Optimization

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