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10th International Symposium on Neural Networks, ISNN 2013

作者： Li, Dong Huang, Kai Zhang, Hanlin Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642390647

In this paper, we propose an algorithm for 12-leads ECG signals feature extraction by Uncorrelated Multilinear Principal Component Analysis(UMPCA). However, traditional algorithms usually base on 2-leads ECG signals and do not efficiently work out for 12-leads signals. Our algorithm aims at the natural 12-leads ECG signals. We firstly do the Short Time Fourier Transformation(STFT) on the raw ECG data and obtain 3rd-order tensors in the spatial-spectral- temporal domain, then take UMPCA to find a Tensor-to-Vector Projection(TVP) for feature extraction. Finally the Support Vector Machine(SVM) classifier is applied to achieve a high accuracy with these features. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Tensors

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Hidden Markov model for action recognition using joint angle acceleration

Hidden Markov model for action recognition using joint angle...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Huang, Sha Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642420504

This paper proposes a recognition method of human actions in video by adding new features, the joint angle acceleration to the feature space. In this method, human body is described as three-dimensional skeletons. The features consist of vectors of several important joint angles on the human body and the joint angle accelerations are also considered as a part of features. Hidden Markov Model (HMM) is used as classification scheme. The HMM models are trained by sequences extracted from the CMU graphics lab motion capture database 1. This method is invariant to scale, coordinate system and transition. A system is implemented to recognize 4 different types of actions (walk, run, jump and jumping jack) both on the dataset of CMU and Weizmann[7]. Each video clip contains a single action type. The experimental results show excellent performance of the proposed approach. A maximum 10.3% accuracy gain can be achieved by our method compared with the method without considering acceleration. © Springer-Verlag 2013.

关键词： Hidden Markov models

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An interpretation of Erlang into value-passing calculus

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Journal of Networks 2013年第7期8卷 1504-1513页

作者： Huang, Hao Yang, Fei Department of Computer Science Shanghai Jiaotong University MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems China

In this paper we present a new process calculus VPCΣ and an interpretation for core Erlang. VPCΣ is at least as expressive as VPC and it is more effective for verification with some built-in functions. The wellestablished symbolic bisimulation in value-passing calculus is now helpful for solving the infinite-state space problem of data values in equivalence checking and verfication. Compared to the previous formalization work of modeling core Erlang in π-calculus, the new interpretation has the following main merits: some essential features for Erlang are implemented faithfully;and above all the soundness of the interpretation is proved with respect to late symbolic bisimulation. © 2013 ACADEMY PUBLISHER.

关键词： Calculations

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Image denoising based on overcomplete topographic sparse coding

Image denoising based on overcomplete topographic sparse cod...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Zhao, Haohua Luo, Jun Huang, Zhiheng Nagumo, Takefumi Murayama, Jun Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Dep. of Computer Science and Engineering Shanghai Jiao Tong Univ. Shanghai China SONY Corporation Tokyo Japan

ISBN: (纸本)9783642420504

This paper presents a novel image denoising framework using overcomplete topographic model. To adapt to the statistics of natural images, we impose sparseness constraints on the denoising model. Based on the overcomplete topographic model, our denoising system improves over previous work on the following aspects: multi-category based sparse coding, adaptive learning, local normalization, and shrinkage function. A large number of simulations have been performed to show the performance of the modified model, demonstrating that the proposed model achieves better denoising performance. © Springer-Verlag 2013.

关键词： Shrinkage

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Labeled Alignment for Recognizing Textual Entailment 6

Labeled Alignment for Recognizing Textual Entailment

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6th International Joint Conference on Natural Language Processing, IJCNLP 2013

作者： Wang, Xiao-Lin Zhao, Hai Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9784990734800

Recognizing Textual Entailment (RTE) is to predict whether one text fragment can semantically infer another, which is required across multiple applications of natural language processing. The conventional alignment scheme, which is developed for machine translation, only marks the paraphrases and hyponyms to justify the entailment pairs, while provides less support for the non-entailment ones. This paper proposes a novel alignment scheme, named labeled alignment, to address this problem, which introduces negative links to explicitly mark the contradictory expressions to justify the non-entailment pairs. Thus the alignment-based RTE method employing the proposed scheme, compared with those employing the conventional one, can gain accuracy improvement through actively detecting the signals of non-entailment. The experimental results on the data sets of two shared RTE tasks indicate the implemented system significantly outperforms both the baseline system and all the other submitted systems. © IJCNLP *** right reserved.

关键词： Alignment

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Grammatical error correction as multiclass classification with single model 17

Grammatical error correction as multiclass classification wi...

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17th Conference on Computational Natural Language Learning: Shared Task, CoNLL 2013

作者： Jia, Zhongye Wang, Peilu Zhao, Hai MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China

ISBN: (纸本)9781937284718

This paper describes our system in the shared task of CoNLL-2013. We illustrate that grammatical error detection and correction can be transformed into a multiclass classification task and implemented as a single-model system regardless of various error types with the aid of maximum entropy modeling. Our system achieves the F1 score of 17.13% on the standard test set. © 2013 Association for Computational Linguistics.

关键词： Error correction

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KySS 1.0: a Framework for Automatic Evaluation of Chinese Input Method Engines 6

KySS 1.0: a Framework for Automatic Evaluation of Chinese In...

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6th International Joint Conference on Natural Language Processing, IJCNLP 2013

作者： Jia, Zhongye Zhao, Hai MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China

ISBN: (纸本)9784990734800

Chinese Input Method Engine (IME) plays an important role in Chinese language processing. However, it has been subjected to lacking a proper evaluation metric for a long time. The natural metric for IME is user experience, which is a rather vague goal for research purpose. We propose a novel approach of quantifying user experience by using keystroke count and then correspondingly develop a framework of IME evaluation, which is fast and accurate. With the underlying linguistic background, the proposed evaluation framework can properly model the user behavior as Chinese is input through English keyboard. It is helpful to point out a way to improve the current Chinese IME performance. © IJCNLP *** right reserved.

关键词： Engines

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Converting continuous-space language models into N-gram language models for statistical machine translation

Converting continuous-space language models into N-gram lang...

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2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013

作者： Wang, Rui Utiyama, Masao Goto, Isao Sumita, Eiichro Zhao, Hai Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong Unviersity Shanghai200240 China Multilingual Translation Laboratory MASTAR Project National Institute of Information and Communications Technology 3-5 Hikaridai Keihanna Science City Kyoto619-0289 Japan MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong Unviersity Shanghai200240 China

ISBN: (纸本)9781937284978

Neural network language models, or continuous-space language models (CSLms), have been shown to improve the performance of statistical machine translation (SMT) when they are used for reranking n-best translations. However, CSLms have not been used in the first pass decoding of SMT, because using CSLms in decoding takes a lot of time. In contrast, we propose a method for converting CSLms into back-off n-gram language models (BNLms) so that we can use converted CSLms in decoding. We show that they outperform the original BNLms and are comparable with the traditional use of CSLms in reranking. © 2013 Association for Computational Linguistics.

关键词： Decoding

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NEURAL SUBSTRATES OF MOTOR IMAGERY BASED BRAIN-COMPUTER INTERFACE TRAINING FOR STROKE PATIENTS WITH SEVERE UPPER LIMB PARALYSIS

NEURAL SUBSTRATES OF MOTOR IMAGERY BASED BRAIN-COMPUTER INTE...

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第七届国际物理医学与康复医学学术大会(7th World Congress of the international society of Physical and Rehabilitation Medicine(ISPRM2013)

作者： Mingfen Li Jie Jia Ye Liu Department of Rehabilitation Huashan Hospital Fudan University MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University China

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A fully abstract view for local cause semantics

A fully abstract view for local cause semantics

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7th International Conference on Advances in Grid and Pervasive computing, GPC 2012

作者： Xue, Jianxin Dong, Xiaoju Department of Computer Science MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783642307669

Recent technological trends have pushed concurrency and mobile computing to the mainstream. Too many semantics have been proposed to picture the behavior of concurrent systems, and their relationship has been a hot topic in concurrency. We aim in this paper to bridge two important concurrent semantics, the true concurrency semantics and the interleaving semantics, based on the local cause semantics, in the framework of mobile computing. We enrich the polyadic π-calculus with the local cause semantics, and present a fully abstract, finiteness-respecting encoding from the local cause polyadic π-calculus to the polyadic π-calculus. Therefore, the local cause bisimulation is reduced to the observation bisimulation. Moreover, a new decidable approach is proposed for the local cause bisimulation on finite processes. © 2012 Springer-Verlag.

关键词： Semantics

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