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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013

作者： Jin, Xin Zhuang, Fuzhen Wang, Shuhui He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9783642409905

Real-world problems usually exhibit dual-heterogeneity, i.e., every task in the problem has features from multiple views, and multiple tasks are related with each other through one or more shared views. To solve these multi-task problems with multiple views, we propose a shared structure learning framework, which can learn shared predictive structures on common views from multiple related tasks, and use the consistency among different views to improve the performance. An alternating optimization algorithm is derived to solve the proposed framework. Moreover, the computation load can be dealt with locally in each task during the optimization, through only sharing some statistics, which significantly reduces the time complexity and space complexity. Experimental studies on four real-world data sets demonstrate that our framework significantly outperforms the state-of-the-art baselines. © 2013 Springer-Verlag.

关键词： Learning systems

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A motivational system for mind model CAM

A motivational system for mind model CAM

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2013 AAAI Fall Symposium

作者： Shi, Zhongzhi Zhang, Jianhua Yue, Jinpeng Qi, Baoyuan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781577356417

A motivation model is proposed in the paper. Based on the model we develop a motivational system for mind model CAM. Through the application in automatic navigation of animal robots shows the motivation system is useful to solve the dynamic and complexity automatic problem. Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Motivation

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Concept learning for cross-domain text classification: A general probabilistic framework

Concept learning for cross-domain text classification: A gen...

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Zhuang, Fuzhen Luo, Ping Yin, Peifeng He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Hewlett Packard Labs China Pennsylvania State University United States

ISBN: (纸本)9781577356332

Cross-domain learning targets at leveraging the knowledge from source domains to train accurate models for the test data from target domains with different but related data distributions. To tackle the challenge of data distribution difference in terms of raw features, previous works proposed to mine high-level concepts (e.g., word clusters) across data domains, which shows to be more appropriate for classification. However, all these works assume that the same set of concepts are shared in the source and target domains in spite that some distinct concepts may exist only in one of the data domains. Thus, we need a general framework, which can incorporate both shared and distinct concepts, for cross-domain classification. To this end, we develop a probabilistic model, by which both the shared and distinct concepts can be learned by the EM process which optimizes the data likelihood. To validate the effectiveness of this model we intentionally construct the classification tasks where the distinct concepts exist in the data domains. The systematic experiments demonstrate the superiority of our model over all compared baselines, especially on those much more challenging tasks.

关键词： Classification (of information)

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Phrase filtering for content words in hierarchical phrase-based model

Phrase filtering for content words in hierarchical phrase-ba...

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14th Workshop on Chinese Lexical Semantics, CLSW 2013

作者： Wang, Xing Xie, Jun Song, Linfeng Lv, Yajuan Yao, Jianmin School of Computer Science AndTechnology Soochow University Suzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783642451843

When hierarchical phrase-based statistical machine translation systems are used for language translation, sometimes the translations' content words were lost: source-side content words is empty when translated into target texts during decoding. Although the translations' BLEU score is very high, it is difficult to understand the translations because of the loss of the content words. In this paper, we propose a basic and efficient method for phrase filtering, with which the phrase' content words translation are checked to decide whether to use the phrase in decoding or not. The experimental results show that the proposed method alleviates the problem of the loss content words' and improves the BLEU scores. © 2013 Springer-Verlag.

关键词： Decoding

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Color image segmentation based on dynamic model and power spectrum

Color image segmentation based on dynamic model and power sp...

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International Conference on Materials Science and Manufacturing, ICMSM 2012

作者： Chen, Yupu Qiao, Yuanhua Miao, Jun College of Applied Sciences Beijing University of Technology Beijing 100124 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783037855614

In this paper, the locally coupled neural oscillator model and power spectrum are introduced to solve the color image segmentation problem. Firstly the single neuron oscillator model is developed, the model parameter is set so as to create limit circle simulating the activity of neuron. Then the locally coupled network model is developed, taking R, G, Bas external input separately, the network output three dynamic orbits representing R, G, B for each image point. Lastly, the power spectrum of the orbits is calculated for each image point, the color image is segmented using the calculated power spectrum. The performance is comparable to the results from other segmentation methods. © (2013) Trans Tech Publications, Switzerland.

关键词： Image segmentation

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Wavelet denoising of SAR images corrupted by speckle noise using cycle spinning

Wavelet denoising of SAR images corrupted by speckle noise u...

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2nd International Conference on intelligent Materials, Applied Mechanics and Design Science, IMAMD 2013

作者： Ji, Ming Wei Liu, Yan Li Zhang, De Xiang The Institute of Mechanical and Electrical Engineering of Anhui University of Architecture Hefei 230601 China Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China

ISBN: (纸本)9783037857175

A novel and efficient speckle noise reduction algorithm based on wavelet transform by cycle spinning for removing speckle of unknown variance and minimizing the effect of pseudo-Gibbs phenomena from Synthetic Aperture Radar (SAR) images is proposed. Therefore, we show that the sub-band decompositions of logarithmically transformed SAR images. Then, we process and reconstruct multi-resolution wavelet coefficients by wavelet-threshold using cycle spinning, a technique estimating the true images as the linear average of individual estimates derived from wavelet thresholded translated versions of the noise images. Experimental results show that the proposed de-noising algorithm is possible to achieve an excellent balance between suppresses speckle effectively and weaken as many image Gibbs phenomena as possible. Quantitative and qualitative comparisons of the results obtained by the new method with the results achieved from the other speckle noise reduction techniques demonstrate its higher performance for speckle reduction in SAR images. © (2013) Trans Tech Publications, Switzerland.

关键词： Wavelet transforms

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Refining image annotation by integrating PLSA with random walk model

Refining image annotation by integrating PLSA with random wa...

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19th International Conference on Advances in Multimedia Modeling, MMM 2013

作者： Tian, Dongping Zhao, Xiaofei Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of the Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9783642357244

In this paper, we present a new method for refining image annotation by integrating probabilistic latent semantic analysis (PLSA) with random walk (RW) model. First, we construct a PLSA model with asymmetric modalities to estimate the posterior probabilities of each annotating keywords for an image, and then a lab.l similarity graph is constructed by a weighted linear combination of lab.l similarity and visual similarity. Followed by a random walk process over the lab.l graph is employed to further mine the correlation of the keywords so as to capture the refining annotation, which plays a crucial role in semantic based image retrieval. The novelty of our method mainly lies in two aspects: exploiting PLSA to accomplish the initial semantic annotation task and implementing random walk process over the constructed lab.l similarity graph to refine the candidate annotations generated by the PLSA. Compared with several state-of-the-art approaches on Corel5k and Mirflickr25k datasets, the experimental results show that our approach performs more efficiently and accurately. © Springer-Verlag 2013.

关键词： Image annotation

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15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

作者： Shang, Tianfeng He, Qing Zhuang, Fuzhen Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate School Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9783642374005

Collab.rative filtering is one of the most popular techniques in recommender systems, and the key point is to find similar users and items. There are already some similarity measures, such as vector cosine similarity and Pearson's correlation coefficient, and so on. However, in some cases, what recommender systems get are not the ratings, but preference sequences of users on a series of items. For this type of data, those traditional similarity measures may fail to meet the practical application requirements. In this paper, a similarity measure based on inversion is proposed for preference sequences naturally. Based on the Inversion similarity measure, some structural information of user preference sequences is analyzed. By merging average precision and weighted inversion into similarity computation, a new similarity measure based on preference sequences is proposed for collab.rative filtering. Experimental results show that the proposed similarity measure based on preference sequences outperforms the common similarity measures on the datasets with continuous real numbers. © 2013 Springer-Verlag.

关键词： Collab.rative filtering

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A reputation management approach for resource constrained trustee agents

A reputation management approach for resource constrained tr...

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Yu, Han Miao, Chunyan An, Bo Leung, Cyril Lesser, Victor R. Nanyang Technological University Singapore Singapore Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China University of British Columbia Canada University of Massachusetts Amherst United States

ISBN: (纸本)9781577356332

Trust is an important mechanism enabling agents to self-police open and dynamic multi-agent systems (ODMASs). Trusters evaluate the reputation of trustees based on their past observed performance, and use this information to guide their future interaction decisions. Existing trust models tend to concentrate trusters' interactions on a small number of highly reputable trustees to minimize risk exposure. When a trustee's servicing capacity is limited, such an approach may cause long delays for trusters and subsequently damage the reputation of trustees. To mitigate this problem, we propose a reputation management approach for trustee agents based on distributed constraint optimization. It helps a trustee to make situation-aware decisions on which incoming requests to serve and prevent the resulting reputation score from being affected by factors out of the trustee's control. The approach is evaluated through theoretical analysis and within a simulated, highly dynamic multi-agent environment. The results show that it can achieve close to optimally efficient utilization of the trustee agents' collective capacity in an ODMAS, promotes fair treatment of trustee agents based on their behavior, and significantly outperforms related work in enhancing social welfare.

关键词： Multi agent systems

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information spreading dynamics of the superspreaders in large opportunistic networks

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Journal of Computational information Systems 2013年第18期9卷 7141-7146页

作者： Yang, Wanchun Hu, Ke Zhou, Shouli Coll. of Information Eng. and Key Lab. of Intelligent Computing and Information Proc. of Edu. Min. Xiangtan University Xiangtan 411105 China Department of Physics Xiangtan University Xiangtan 411105 China College of Information Engineering Zhejiang Univ. of Technology Hangzhou 310023 China

The nodes with large degree exhibit a powerful information spreading capability in networks. It is always obvious that the popularity nodes can spread the information to more people in opportunistic networks. Many researchers try to speed up the spreading velocity by the popularity nodes. In this paper the information spreading dynamics in opportunistic networks is investigated. It is found that when the number of the network nodes is large enough, the convergence time will be approaching no matter which node first initiated the message propagation. But when the node number of the networks is small in opportunistic networks, the convergence time varies greatly when the messages are initiated by nodes with different node degree. The theory proof and the simulation results are given in this paper. © 2013 Binary information Press.

关键词： Dynamics

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