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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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Robust Bayesian max-margin clustering 14

Robust Bayesian max-margin clustering

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Proceedings of the 28th International Conference on Neural Information Processing systems - Volume 1

作者： Changyou Chen Jun Zhu Xinhua Zhang Dept. of Electrical and Computer Engineering Duke University Durham NC State Key Lab of Intelligent Technology & Systems Tsinghua National TNList Lab and Dept. of Computer Science & Tech. Tsinghua University Beijing China Australian National University (ANU) and National ICT Australia (NICTA) Canberra Australia

We present max-margin Bayesian clustering (BMC), a general and robust framework that incorporates the max-margin criterion into Bayesian clustering models, as well as two concrete models of BMC to demonstrate its flexibility and effectiveness in dealing with different clustering tasks. The Dirichlet process max-margin Gaussian mixture is a nonparametric Bayesian clustering model that relaxes the underlying Gaussian assumption of Dirichlet process Gaussian mixtures by incorporating max-margin posterior constraints, and is able to infer the number of clusters from data. We further extend the ideas to present max-margin clustering topic model, which can learn the latent topic representation of each document while at the same time cluster documents in the max-margin fashion. Extensive experiments are performed on a number of real datasets, and the results indicate superior clustering performance of our methods compared to related baselines.

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An introduction to string re-writing kernel

An introduction to string re-writing kernel

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Bu, Fan Li, Hang Zhu, Xiaoyan State Key Laboratory of Intelligent Technology and Systems Tsinghua University China Tsinghua National Laboratory for Information Sci. and Tech. Tsinghua University China Department of Computer Sci. and Tech. Tsinghua University China Huawei Noah's Ark Lab Hong Kong Hong Kong

ISBN: (纸本)9781577356332

Learning for sentence re-writing is a fundamental task in natural language processing and information retrieval. In this paper, we propose a new class of kernel functions, referred to as string rewriting kernel, to address the problem. A string re-writing kernel measures the similarity between two pairs of strings. It can capture the lexical and structural similarity between sentence pairs without the need of constructing syntactic trees. We further propose an instance of string re-writing kernel which can be computed efficiently. Experimental results on benchmark datasets show that our method can achieve comparable results with state-of-the-art methods on two sentence re-writing learning tasks: paraphrase identification and recognizing textual entailment.

关键词： Natural language processing systems

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Scalable Inference for Logistic-Normal Topic Models 13

Scalable Inference for Logistic-Normal Topic Models

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Annual Conference on Neural Information Processing systems

作者： Jianfei Chen Jun Zhu Zi Wang Xun Zheng Bo Zhang State Key Lab of Intelligent Tech. & Systems Tsinghua National TNList Lab Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9781632660244

Logistic-normal topic models can effectively discover correlation structures among latent topics. However, their inference remains a challenge because of the non-conjugacy between the logistic-normal prior and multinomial topic mixing proportions. Existing algorithms either make restricting mean-field assumptions or are not scalable to large-scale applications. This paper presents a partially collapsed Gibbs sampling algorithm that approaches the provably correct distribution by exploring the ideas of data augmentation. To improve time efficiency, we further present a parallel implementation that can deal with large-scale applications and learn the correlation structures of thousands of topics from millions of documents. Extensive empirical results demonstrate the promise.

关键词： time efficiency Scalability algorithms Themes Mix proportioning Gibbs Sampling large sizes

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A hop-by-hop network coding algorithm for aviation communications networks

A hop-by-hop network coding algorithm for aviation communica...

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2012 2nd IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012

作者： Wang, Yuan Xu, Hua Jia, Pei-Fa State Key Lab of Intelligent Technology and Systems Tsinghua University Beijing 100084 China Tsinghua National Lab for Information Sci. and Tech. Tsinghua University Beijing 100084 China Department of Computer Sci. and Tech. Tsinghua University Beijing 100084 China Communication Institute Air Force Equipment Academy Beijing 100085 China

ISBN: (纸本)9781467321938

Considering the feature of intensive node mobility in aviation communication networks, a hop-by-hop network coding algorithm based on Ad Hoc networks is proposed in this paper. A typical network was built in a network simulator, and receiving accuracy rate and receiving delay were collected, to analyze the performance of the proposed algorithm in scalable networks with different traffic modeling. The simulation results prove that the presented algorithm has better performance in enhancing receiving accuracy rate and shortening receiving delay, compared with traditional networks without network coding. It also applies to both bidirectional and directional traffic flows, and achieves better performance in large-scale networks. Therefore, this algorithm has great potentials in large-scale multi-hop aviation communication networks. © 2012 IEEE.

关键词： Network coding

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Model-based bridge recognition in high resolution SAR image

Model-based bridge recognition in high resolution SAR image

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MIPPR 2009 - Automatic Target Recognition and Image Analysis: 6th International Symposium on Multispectral Image Processing and Pattern Recognition

作者： Pei, Deli Sun, Fuchun Wang, Hongqiao Chen, Ning Department of Computer Science and Technology Tsinghua University Beijing 100084 China State Key Lab. of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing 100084 China Xi'an High Tech. Research Institute Xi'an Shanxi 710025 China

ISBN: (纸本)9780819478061

A new bridge recognition method in Synthetic Aperture Radar (SAR) image using bridge model and SVM is presented in this paper. Firstly, water region is extracted from original SAR image by self-adapt segmentation and mathematic morphological method. Then based on bridge model, the bridge candidates in water region can be found out and their texture feature can also be ***, with the usage of SVM, whether these objects are bridges or not can be identified and the real bridges can be mark ed in the SAR image, as well as the corresponding information such as position. Experiment results show that, with the help of water region segmentation and bridge model, the efficiency of the algorithm is greatly promoted, meanwhile, the recognition accuracy is guaranteed by high quality classifier of SVM. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Synthetic aperture radar

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Web image clustering based-on Multi-Instance

Web image clustering based-on Multi-Instance

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2008 IEEE/WIC/ACM International Conference on Web Intelligence and intelligent Agent technology - Workshops, WI-IAT Workshops 2008

作者： Lu, Jing Ma, Shaoping Zhang, Min State Key Lab. of Intelligent Tech. and Systems Tsinghua National Lab. for Information Science and Tech. Department of Computer Science and Tech. Tsinghua Uni Beijing 100084 China

ISBN: (纸本)9780769534961

In image retrieval and annotation, Multi-Instance Learning has been studied actively. Most of the methods solve the MIL problem in a supervised way. In this paper, we proposed two unsupervised frameworks for clustering multi-instance objects based on Expectation Maximization (EM) and iterative heuristic optimization respectively. For each framework, we introduced three new algorithms of finding users' interests on specific web images without any manual labeled data. And comparative studies have shown the effectiveness of the proposed algorithms. © 2008 IEEE.

关键词： Maximum principle

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Regularized clustering for documents

Proceedings of the 30th Annual International ACM SIGIR Confe...

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Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07 2007年 95-102页

作者： Wang, Fei Zhang, Changshui Li, Tao State Key Lab of Intelligent Tech. and Systems Department of Automation Tsinghua University Beijing 100084 China School of Computer Science Florida International University Miami FL 33199 United States

ISBN: (纸本)1595935975

In recent years, document clustering has been receiving more and more attentions as an important and fundamental technique for unsupervised document organization, automatictopic extraction, and fast information retrieval or filtering. In this paper, we propose a novel method for clustering documents using regularization. Unlike traditional globally regularized clustering methods, our method first construct a local regularized linear label predictor for each document vector, and then combine all those local regularizers with a global smoothness regularizer. So we call our algorithm Clustering with Local and Global Regularization (CLGR). We will show that the cluster memberships of the documents can be achieved by eigenvalue decomposition of a sparse symmetric matrix, which can be efficiently solved by iterative methods. Finally our experimental evaluations on several datasets are presented to show the superiorities of CLGR over traditional document clustering methods. Copyright 2007 ACM.

关键词： Information retrieval

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SAR image ATR using SVM with a low dimensional combined feature

SAR image ATR using SVM with a low dimensional combined feat...

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5th International Symposium on Multispectral Image Processing and Pattern Recognition

作者： Wang, Hongqiao Sun, Fuchun Zhao, Zongtao Cai, Yanning Tsinghua Univ Dept Comp Sci & Technol State Key Lab Intelligent Technol & Systems Beijing 100084 Peoples R China Xian Res Inst Hi Tech Command Automat Dept Xian Peoples R China

ISBN: (纸本)9780819469502

In this paper, a grayscale wavelet moment and entropy combined feature, which can well represent the images with much lower dimensions, is proposed for the MSTAR targets' classification, also a discriminative feature selection and evaluation method for multi-class targets is presented. By introducing SVM as the classifier to some simulation tests, it can be shown that the grayscale wavelet moment and entropy combined feature has good capability for translation, scaling and rotation transformation in both local information and global information conditions, by the reasons of wavelet moments' multi-resolution analysis, moment invariant quality and entropy's statistic quality for image disorder. The test also confirms that this feature has a significant improvement on classificatory accuracy using SVM with a lower feature dimension than the other features such as the single wavelet moment, Hu's moment and PCA.

关键词： SAR ATR MSTAR wavelet moment entropy SVM PCA

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A secure image authentication algorithm with pixel-level tamper localization

A secure image authentication algorithm with pixel-level tam...

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2004 International Conference on Image Processing, ICIP 2004

作者： Wu, Jinhai Zhu, Bin B. Li, Shipeng Lin, Fuzong State Key Lab of Intelligent Tech. and Systems Tsinghua Univ. Beijing 100084 China Microsoft Research Asia Beijing 100080 China

ISBN: (纸本)0780385543

In this paper, we use a generalized model for all the previously proposed pixel-wise authentication schemes. Then we show how this model can be compromised with an oracle attack. This motivated us to develop a novel authentication scheme to be described here. The new scheme is designed to detect any changes to a signal. It consists of two mechanisms dedicated to authenticity verification for a signal and localization of tampered pixels, respectively. The scheme is secure yet maintains the fine tamper localization capability of a pixel-wise scheme. Experimental results show that the proposed scheme has a good accuracy in locating tampered pixels. ©2004 IEEE.

关键词： Image analysis

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