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PPLSA: Parallel probabilistic latent semantic analysis based on MapReduce

PPLSA: Parallel probabilistic latent semantic analysis based...

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7th IFIP International Conference on intelligent information processing, IIP 2012

作者： Li, Ning Zhuang, Fuzhen He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate University Chinese Academy of Sciences Beijing China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding China

ISBN: (纸本)9783642328909

PLSA(Probabilistic Latent Semantic Analysis) is a popular topic modeling technique for exploring document collections. Due to the increasing prevalence of large datasets, there is a need to improve the scalab.lity of computation in PLSA. In this paper, we propose a parallel PLSA algorithm called PPLSA to accommodate large corpus collections in the MapReduce framework. Our solution efficiently distributes computation and is relatively simple to implement. © 2012 IFIP International Federation for information processing.

关键词： MapReduce

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Pattern Synthesis of MIMO Radar Based on Immune Differential Evolution Algorithm

Pattern Synthesis of MIMO Radar Based on Immune Differential...

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2020 International Conference on Modeling, Big Data Analytics and Simulation, MBDAS 2020

作者： Jiang, Ling Jiang, Yi Chen, Guangfu Shi, Guimin Cheng, Qi School of Mathematics and Computer Wuyi University Wuyishan354300 China Key Lab. of Cogn. Computing and Intelligent Information Processing of Fujian Education Institutions Wuyishan354300 China Big Data Development Administration of Anji County Huzhou313000 China

In order to optimize the pattern synthesis of multiple input and multiple output (MIMO) radar, immune mechanism is adopted to overcome the premature risk of differential evolution (DE) algorithm, namely immune differential evolution (IDE). Firstly, the modeling of MIMO radar is introduced by encoding the position of array in the binary. Secondly, the immune mechanism is employed to improve the DE. In IDE, two parameters are self-adapted for the mutation operator by immune mechanism to enhance the convergence ability of DE, including scaling factor and crossover rate. Several experiments are conducted to analysis the performance of IDE. The simulation results show that the IDE with variable parameters can get optimal results in MIMO radar with lower the peak side-lobe level (PSLL) and maintain the diversity with stronger convergence ability and shorter calculation speed. © Published under licence by IOP Publishing Ltd.

关键词： Optimization

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Bilingually-constrained (monolingual) shift-reduce parsing

Bilingually-constrained (monolingual) shift-reduce parsing

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2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Huang, Liang Jiang, Wenbin Liu, Qun Google Research 1350 Charleston Rd. Mountain View CA 94043 United States Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

Jointly parsing two languages has been shown to improve accuracies on either or both sides. However, its search space is much bigger than the monolingual case, forcing existing approaches to employ complicated modeling and crude approximations. Here we propose a much simpler alternative, bilingually-constrained monolingual parsing, where a source-language parser learns to exploit reorderings as additional observation, but not bothering to build the target-side tree as well. We show specifically how to enhance a shift-reduce dependency parser with alignment features to resolve shift-reduce conflicts. Experiments on the bilingual portion of Chinese Treebank show that, with just 3 bilingual features, we can improve parsing accuracies by 0.6% (absolute) for both English and Chinese over a state-of-the-art baseline, with negligible (∼6%) efficiency overhead, thus much faster than biparsing. © 2009 ACL and AFNLP.

关键词： Forestry

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A cascaded linear model for joint Chinese word segmentation and part-of-speech tagging

A cascaded linear model for joint Chinese word segmentation ...

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46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT

作者： Jiang, Wenbin Huang, Liang Liu, Qun Lü, Yajuan Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China Department of Computer and Information Science Levine Hall University of Pennsylvania 3330 Walnut Street Philadelphia PA 19104 United States

ISBN: (纸本)9781932432046

We propose a cascaded linear model for joint Chinese word segmentation and partof- speech tagging. With a character-based perceptron as the core, combined with realvalued features such as language models, the cascaded model is able to efficiently utilize knowledge sources that are inconvenient to incorporate into the perceptron directly. Experiments show that the cascaded model achieves improved accuracies on both segmentation only and joint segmentation and part-of-speech tagging. On the Penn Chinese Treebank 5.0, we obtain an error reduction of 18.5% on segmentation and 12% on joint segmentation and part-of-speech tagging over the perceptron-only baseline. © 2008 Association for Computational Linguistics.

关键词： Computational linguistics

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Efficient incremental decoding for tree-to-string translation

Efficient incremental decoding for tree-to-string translatio...

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Conference on Empirical Methods in Natural Language processing, EMNLP 2010

作者： Huang, Liang Mi, Haitao Information Sciences Institute University of Southern California 4676 Admiralty Way Marina del Rey CA 90292 United States Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

ISBN: (纸本)1932432868

Syntax-based translation models should in principle be efficient with polynomially-sized search space, but in practice they are often embarassingly slow, partly due to the cost of language model integration. In this paper we borrow from phrase-based decoding the idea to generate a translation incrementally left-to-right, and show that for tree-to-string models, with a clever encoding of derivation history, this method runs in average-case polynomial-time in theory, and linear-time with beam search in practice (whereas phrase-based decoding is exponential-time in theory and quadratic-time in practice). Experiments show that, with comparable translation quality, our tree-to-string system (in Python) can run more than 30 times faster than the phrase-based system Moses (in C++). © 2010 Association for Computational Linguistics.

关键词： Decoding

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Forest-based translation

Forest-based translation

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46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT

作者： Mi, Haitao Huang, Liang Liu, Qun Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China Department of Computer and Information Science Levine Hall University of Pennsylvania 3330 Walnut Street Philadelphia PA 19104 United States

ISBN: (纸本)9781932432046

Among syntax-based translation models, the tree-based approach, which takes as input a parse tree of the source sentence, is a promising direction being faster and simpler than its string-based counterpart. However, current tree-based systems suffer from a major drawback: they only use the 1-best parse to direct the translation, which potentially introduces translation mistakes due to parsing errors. We propose a forest-based approach that translates a packed forest of exponentially many parses, which encodes many more alternatives than standard n-best lists. Large-scale experiments show an absolute improvement of 1.7 BLEU points over the 1-best baseline. This result is also 0.8 points higher than decoding with 30-best parses, and takes even less time. © 2008 Association for Computational Linguistics.

关键词： Syntactics

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Exploring multi-loss function based attention framework for vehicle re-identification 10

Exploring multi-loss function based attention framework for ...

引用

10th International Conference on information Technology in Medicine and Education, ITME 2019

作者： Liu, Wei Zhang, Yi Luo, Zhiming Li, Shaozi East China Jiaotong University Jiangxi China Cognitive Science Department Xiamen University Fujian China Postdoc Center of Information and Communication Engineering Xiamen University China Key Lab. of Cogn. Computing and Intelligent Information Processing of Fujian Education Institutions Wuyishan China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering Yi Chang China

ISBN: (纸本)9781728139173

Vehicle Re-identification(Re-ID) refers to the task of matching a specific vehicle across multiple non-overlapping cameras. Precise vehicle Re-ID suffers from two main challenges: (1) different vehicle identities with a similar appearance of the same type have a subtle inter-instance discrepancy, (2) one vehicle usually has large intra-instance differences due to viewpoint and illumination variations. To address these challenges, in this paper, we proposed an Attention-based Framework for Vehicle Re-ID named AFVR, which combines the benefits of both the cross-entropy loss function and the triplet loss function. Experimental results on two popular vehicle Re-ID benchmarks demonstrate the effectiveness of our proposed method, compared with the state of the arts. © 2019 IEEE.

关键词： Vehicles

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Leaf image recognition using Fourier transform based on ordered sequence

Leaf image recognition using Fourier transform based on orde...

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8th International Conference on intelligent computing Technology, ICIC 2012

作者： Yang, Li-Wei Wang, Xiao-Feng Department of Automation University of Science and Technology of China Hefei Anhui 230027 China Intelligent Computing Laboratory Hefei Institute of Intelligent Machines Chinese Academy of Sciences P.O. Box 1130 Hefei Anhui 230031 China Key Lab. of Network and Intelligent Information Processing Hefei University Hefei Anhui 230601 China

ISBN: (纸本)9783642315879

There are a number of leaf recognition methods, but most of them are based on Euclidean space. In this paper, we will introduce a new description of feature for the leaf image recognition, which represents the leaf contour with the ordered sequence. For a leaf image, points on the contour represent the most important information of the leaf. Thus, by extracting serial points of the leaf contour, the unique corresponding ordered sequence can be obtained for a contour. Then, we can compute the amplitude-frequency feature by performing the Discrete Fourier transform on the ordered sequence. Since the low-frequency part of the Fourier transform represents the global information and the high-frequency part the local details, we can adopt the amplitude-frequency feature for leaf image recognition. Experimental results on the famous Swedish library and ICL library show that the proposed feature is effective for leaf image recognition. © 2012 Springer-Verlag.

关键词： Image recognition

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Application of AWE to scattering analysis of the double-negative medium

Application of AWE to scattering analysis of the double-nega...

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2010 9th International Symposium on Antennas Propagation and EM Theory, ISAPE 2010

作者： Sun, Yu-Xin Chen, Ming-Sheng Wu, Xian-Liang Yang, Mei Wang, Hui Key Lab. of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei China Department of Physics and Electronic Engineering Hefei Normal University Hefei China School of Information Science and Technology University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9781424469062

The PMCHWT equation of the double negative media (DNG) is obtained based on its constitutive relationship. And the surface currents and radar cross section (RCS) at a single frequency point is computed by Method of moments (MOM). The asymptotic waveform evaluation (AWE) technique for dispersive dielectric medium is deduced and apllied to electromagnetic scattering analysis of double-negative medium within a given frequency band. ©2010 IEEE.

关键词： Method of moments

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Benchmarking still-to-video face recognition via partial and local linear discriminant analysis on COX-S2V dataset

Benchmarking still-to-video face recognition via partial and...

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11th Asian Conference on Computer Vision, ACCV 2012

作者： Huang, Zhiwu Shan, Shiguang Zhang, Haihong Lao, Shihong Kuerban, Alifu Chen, Xilin Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China OMRON Social Solutions Co. Ltd. Kyoto Japan College of Information Science and Engineering Xinjiang University China

ISBN: (纸本)9783642374432

In this paper, we explore the real-world Still-to-Video (S2V) face recognition scenario, where only very few (single, in many cases) still images per person are enrolled into the gallery while it is usually possible to capture one or multiple video clips as probe. Typical application of S2V is mug-shot based watch list screening. Generally, in this scenario, the still image(s) were collected under controlled environment, thus of high quality and resolution, in frontal view, with normal lighting and neutral expression. On the contrary, the testing video frames are of low resolution and low quality, possibly with blur, and captured under poor lighting, in non-frontal view. We reveal that the S2V face recognition has been heavily overlooked in the past. Therefore, we provide a benchmarking in terms of both a large scale dataset and a new solution to the problem. Specifically, we collect (and release) a new dataset named COX-S2V, which contains 1,000 subjects, with each subject a high quality photo and four video clips captured simulating video surveillance scenario. Together with the database, a clear evaluation protocol is designed for benchmarking. In addition, in addressing this problem, we further propose a novel method named Partial and Local Linear Discriminant Analysis (PaLo-LDA). We then evaluated the method on COX-S2V and compared with several classic methods including LDA, LPP, ScSR. Evaluation results not only show the grand challenges of the COX-S2V, but also validate the effectiveness of the proposed PaLo-LDA method over the competitive methods. © 2013 Springer-Verlag.

关键词： Benchmarking

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