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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Sun, Hui Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE Key Laboratory of Systems Biomedicine Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9783642344770

Fatigue is the most important reason leading to traffic accidents. In order to ensure traffic safety, various methods based on electroencephalogram (EEG) are proposed. But most of them, either regression or classification, are focused on the relationship between feature space and observation values, so the changing patterns of features are ignored or discarded. In this paper, we propose a new fatigue classification method by using parallel hidden-Markov-model and pattern classifier combination techniques, where each model represents a particular fatigue-high-related feature. In the experiment, subjects are asked to accomplish some simple tasks, and both their fatigue states and their EEG signals are recorded simultaneously. Experimental results indicate that the mean error rate obtained by using our new method are 11.15% for classifying 3 states and 16.91% for classifying 4 states, respectively, while the existing approach can only reach 16.45% and 23.55% under the same condition. © 2012 Springer-Verlag.

关键词： Electroencephalography

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Parallel Learning of Large-scale Multi-Label Classification Problems with Min-Max Modular LIBLINEAR

Parallel Learning of Large-scale Multi-Label Classification ...

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International Joint Conference on Neural Networks

作者： Yangyang Chen Bao-Liang Lu Hai Zhao Department of Computer Science and Engineering and MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University

ISBN: (纸本)9781467314886

The study on pattern classification trends to be towards large-scale, multi-label, and imbalanced problems. The amount of the data which need to be classified is typically dozens of millions and it keeps rapid increasing in recent years. Traditional pattern classification approaches are inefficient and even ineffective in this situation. In our previous work, we proposed a min-max modular (M~3) network for dealing with large-scale and imbalanced problems. M~3-network is a generalized modular learning framework and includes three main steps: decomposing a large-scale problem into several smaller independent sub-problems, learning these sub-problems in parallel, and combining the results of the sub-problems to generate a solution to the original problem. In this paper, we embed LIBLINEAR into M~3-network (M3-liblnear) to deal with large-scale, multi-label, and imbanlanced pattern classification problems. LIBLINEAR is a fast implementation of a linear classifier. M~3-Liblinear uses LIBLINEAR as a base classifier to learn each of the sub-problems. We compare M~3-Liblinear with Liblinear-cdblock on a large-scale Japanese patent classification problem. Experimental results demonstrate that M~3-Liblinear is superior to Liblinearcd-block in both training time and generalization performance.

关键词： Min-max modular network Liblinear-cdblock Multi-label problem Imbalanced problem Pattern recognition large sizes Modularity Parallel Lines original problem

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On Real Reward Testing

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Journal of Shanghai Jiaotong university(Science) 2011年第4期16卷 479-484页

作者：杨伟忠邓玉欣 MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiaotong University

We extend the traditional nonnegative reward testing with negative *** this new testing framework,may preorder and must preorder are the inverse of each *** surprisingly,it turns out that the real reward must testing is no more powerful than the nonnegative reward testing,at least for finite processes. In order to prove that result,we exploit an important property of failure simulation about the inclusion of the testing outcomes between two related processes.

关键词： probabilistic processes real reward testing nonnegative reward testing failure simulation

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Chinese Coreference Resolution via Ordered Filtering 12

Chinese Coreference Resolution via Ordered Filtering

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Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

作者： Xiaotian Zhang Chunyang Wu Hai Zhao Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong UniversityMOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University

ISBN: (纸本)9781627484046

We in this paper present the model for our participation (BCMI) in the CoNLL-2012 Shared Task. This paper describes a pure rule-based method, which assembles different filters in a proper order. Different filters handle different situations and the filtering strategies are designed manually. These filters are assigned to different ordered tiers from general to special cases. We participated in the Chinese and English closed tracks, scored 51.83 and 59.24 respectively.

关键词： Coreference Resolution Filtration Filters Ordered Chinese philosophy Chinese Chinese art proper order paper

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Hybrid Rule-based Algorithm for Coreference Resolution 12

Hybrid Rule-based Algorithm for Coreference Resolution

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Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

作者： Heming Shou Hai Zhao Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong UniversityMOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University

ISBN: (纸本)9781627484046

This paper describes our coreference resolution system for the CoNLL-2012 shared task. Our system is based on the Stanford's dcore-f deterministic system which applies multiple sieves with the order from high precision to low precision to generate coreference chains. We introduce the newly added constraints and sieves and discuss the improvement on the o-riginal system. We evaluate the system using OntoNotes data set and report our results of average F-score 58.25 in the closed track.

关键词： Coreference Resolution Sieves sieving

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Break index labeling of mandarin text via syntactic-to-prosodic tree mapping

Break index labeling of mandarin text via syntactic-to-proso...

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International Symposium on Chinese Spoken Language Processing

作者： Xiaotian Zhang Yao Qian Hai Zhao Frank K. Soong Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiaotong University Shanghai China Microsoft Research Asia Beijing China

In this study, we investigate the break index labeling problem with a syntactic-to-prosodic structure conversion. The statistical relationship between the mapped syntactic tree structure and prosodic tree structure of sentences in the training set is used to generate a Synchronous Tree Substitution Grammar (STSG) which can describe the probabilistic mapping (substitution) rules between them. For a given test sentence and the corresponding parsed syntactic tree structure, thus generated STSG can convert the syntactic tree to a prosodic tree statistically. We compare the labeling results with other approaches and show the probabilistic mapping can indeed benefit break index labeling performance.

关键词： IP networks Biological system modeling Pragmatics Abstracts Syntactics

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A fast algorithm for recovery of jointly sparse vectors based on the alternating direction methods

A fast algorithm for recovery of jointly sparse vectors base...

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14th International Conference on Artificial Intelligence and Statistics, AISTATS 2011

作者： Lu, Hongtao Long, Xianzhong Lv, Jingyuan MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

The standard compressive sensing (CS) aims to recover sparse signal from single mea- surement vector which is known as SMV model. By contrast, recovery of sparse signals from multiple measurement vectors is called MMV model. In this paper, we consider the recovery of jointly sparse signals in the MMV model where multiple signal measurements are represented as a matrix and the sparsity of signal occurs in common locations. The sparse MMV model can be formulated as a matrix (2;1)-norm minimization problem, which is much more difficult to solve than the l1-norm minimization in standard CS. In this paper, we propose a very fast algorithm, called MMV-ADM, to solve the jointly sparse signal recovery problem in MMV settings based on the alternating direction method (ADM). The MMV- ADM alternately updates the recovered signal matrix, the Lagrangian multiplier and the residue, and all update rules only involve matrix or vector multiplications and summations, so it is simple, easy to implement and much faster than the state-of-the-art method MMVprox. Numerical simulations show that MMV-ADM is at least dozens of times faster than MMVprox with comparable recovery accuracy. Copyright 2011 by the authors.

关键词： Recovery

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Edgel index for large-scale sketch-based image search

Edgel index for large-scale sketch-based image search

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作者： Cao, Yang Wang, Changhu Zhang, Liqing Zhang, Lei MOE Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University China Microsoft Research Asia Beijing China

ISBN: (纸本)9781457703942

Retrieving images to match with a hand-drawn sketch query is a highly desired feature, especially with the popularity of devices with touch screens. Although query-by-sketch has been extensively studied since 1990s, it is still very challenging to build a real-time sketch-based image search engine on a large-scale database due to the lack of effective and efficient matching/indexing solutions. The explosive growth of web images and the phenomenal success of search techniques have encouraged us to revisit this problem and target at solving the problem of web-scale sketch-based image retrieval. In this work, a novel index structure and the corresponding raw contour-based matching algorithm are proposed to calculate the similarity between a sketch query and natural images, and make sketch-based image retrieval scalable to millions of images. The proposed solution simultaneously considers storage cost, retrieval accuracy, and efficiency, based on which we have developed a real-time sketch-based image search engine by indexing more than 2 million images. Extensive experiments on various retrieval tasks (basic shape search, specific image search, and similar image search) show better accuracy and efficiency than state-of-the-art methods. © 2011 IEEE.

关键词： Efficiency

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A game theoretic model and tree analysis method for fair exchange protocols

A game theoretic model and tree analysis method for fair exc...

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5th International Conference on Theoretical Aspects of Software Engineering, TASE 2011

作者： Li, Guoqiang Gu, Yonggen Tao, Xiuting Tao, Jie School of Software Shanghai Jiao Tong University MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai China School of Information and Engineering Huzhou Teachers College Zhejiang China College of Mathematics Physics and Information Engineering Zhejiang Normal University China

ISBN: (纸本)9780769545066

Exchange protocols are an important theoretic basis to make secure electronic commerce and electronic business transactions possible, in which the fairness is a crucial property. To ensure and verify the property, a specific model is proposed, based on the extensive game with imperfect information. Fairness is built in the protocol game and the corresponding game tree. To verify the property, a tree analysis method is offered, and a linear time algorithm is given. As a case study, some flaws of ASW protocol are found. © 2011 IEEE.

关键词： Game theory

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Preference-Based Top-K Influential Nodes Mining in Social Networks

Preference-Based Top-K Influential Nodes Mining in Social Ne...

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Yunlong Zhang Jingyu Zhou Jia Cheng School of Software MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University Shanghai China

Finding top-K influential nodes in social networks has many important applications. Previous work only considered that one node in the network can influence other nodes with a uniform probability, which doesn't take user preferences into account and greatly affects the accuracy of results. We propose a two-stage mining algorithm (GAUP) for mining most influential nodes on a specific topic. In the first stage, GAUP uses a collaborative filtering technique to determine user preferences on a topic. Then in the second stage, GAUP adopts a greedy algorithm to find top-K nodes in the network. Our evaluation shows that our GAUP algorithm can successfully mine top nodes for a given topic.

关键词： Integrated circuit modeling Greedy algorithms Social network services Approximation methods Adaptation models Approximation algorithms

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