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检索条件"机构=State Key Lab of Intelligent Tech. and Systems"

共 105 条记录，以下是41-50 订阅

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Robust Bayesian max-margin clustering 14

Robust Bayesian max-margin clustering

引用

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

引用

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

引用

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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Transferring planar surface plasmon resonance structures onto fiber end facets and integration with microfluidics

Transferring planar surface plasmon resonance structures ont...

引用

Frontiers in Optics, FIO 2013

作者： He, Xiaolong Long, Jing Yi, Hui Chen, Leng Tang, Yihe Yang, Tian Univ. of Michigan-Shanghai Jiaotong Univ. Joint Institute Natl Key Lab. of Nano/Micro Fabr. Tech. Key Laboratory for Thin Film and Microfabrication of the Ministry of Education State Key Lab of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong Univ. China

Planar arrays of gold nanoslits are efficiently transferred to the end facets of single mode fibers with high quality, using the "glue and strip" method. A microfluidics integrated fiberoptic surface plasmon... 详细信息

ISBN: (纸本)9781557529879

关键词： Microfluidics

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Particle mixed membership stochastic block model

Particle mixed membership stochastic block model

引用

2012 8th International Conference on Semantics, Knowledge and Grids, SKG 2012

作者： Zhang, Yan Jiang, Qixia Sun, Maosong State Key Laboratory on Intelligent Technology and Systems Department of Computer Sci. and Tech. Tsinghua University Beijing 100084 China

ISBN: (纸本)9780769547947

Massive real-world data are network-structured, such as semantic web, social network, relationship between proteins, etc. Modeling a network is an effective way for better understanding the properties of a network, while avoiding the complexity of the full description. This paper proposes a novel hierarchical Bayesian model for relational data, which is an extension of Mixed Membership Stochastic Block model. Unlike previous work assumes edges to be of atomic, our model recognizes that each edge is composed of multiple elementary relationships and the weight on this edge is a includes all the weights of these elementary relationships. This allows our model to incorporate more information about the network and increases its ability of uncertainty tolerance. A fast inference based on variational inference is offered. Empirical results on a synthetic data and three real-world data sets demonstrate the effectiveness and the robustness of our method. © 2012 IEEE.

关键词： Stochastic systems

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String re-writing kernel

String re-writing kernel

引用

50th Annual Meeting of the Association for Computational Linguistics, ACL 2012

作者： Bu, Fan Li, Hang Zhu, Xiaoyan State Key Laboratory of Intelligent Technology and Systems China Tsinghua National Laboratory for Information Sci. and Tech. China Department of Computer Sci. and Tech. Tsinghua University China Microsoft Research Asia No. 5 Danling Street Beijing 100080 China

ISBN: (纸本)9781937284244

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 re-writing kernel, to address the problem. A string re-writing kernel measures the similarity between two pairs of strings, each pair representing re-writing of a string. It can capture the lexical and structural similarity between two pairs of sentences without the need of constructing syntactic trees. We further propose an instance of string rewriting kernel which can be computed efficiently. Experimental results on benchmark datasets show that our method can achieve better results than state-of-the-art methods on two sentence re-writing learning tasks: paraphrase identification and recognizing textual entailment. © 2012 Association for computational Linguistics.

关键词： Natural language processing systems

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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...

引用

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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Left-to-right tree-to-string decoding with prediction

Left-to-right tree-to-string decoding with prediction

引用

2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL 2012

作者： Feng, Yang Liu, Yang Liu, Qun Cohn, Trevor Department of Computer Science University of Sheffield Sheffield United Kingdom State Key Laboratory on Intelligent Technology and Systems Department of Computer Sci. and Tech. Tsinghua University Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781937284435

Decoding algorithms for syntax based machine translation suffer from high computational complexity, a consequence of intersecting a language model with a context free grammar. Left-to-right decoding, which generates the target string in order, can improve decoding efficiency by simplifying the language model evaluation. This paper presents a novel left to right decoding algorithm for tree-to-string translation, using a bottom-up parsing strategy and dynamic future cost estimation for each partial translation. Our method outperforms previously published tree-to-string decoders, including a competing left-to-right method. © 2012 Association for Computational Linguistics.

关键词： Context free grammars

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Monte Carlo methods for maximum margin supervised topic models

Monte Carlo methods for maximum margin supervised topic mode...

引用

26th Annual Conference on Neural Information Processing systems 2012, NIPS 2012

作者： Jiang, Qixia Zhu, Jun Sun, Maosong Xing, Eric P. Department of Computer Science and Technology Tsinghua National TNList Lab China State Key Lab of Intelligent Tech. and Sys. Tsinghua University Beijing 100084 China School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 United States

ISBN: (纸本)9781627480031

An effective strategy to exploit the supervising side information for discovering predictive topic representations is to impose discriminative constraints induced by such information on the posterior distributions under a topic model. This strategy has been adopted by a number of supervised topic models, such as MedLDA, which employs max-margin posterior constraints. However, unlike the likelihood-based supervised topic models, of which posterior inference can be carried out using the Bayes' rule, the max-margin posterior constraints have made Monte Carlo methods infeasible or at least not directly applicable, thereby limited the choice of inference algorithms to be based on variational approximation with strict mean field assumptions. In this paper, we develop two efficient Monte Carlo methods under much weaker assumptions for max-margin supervised topic models based on an importance sampler and a collapsed Gibbs sampler, respectively, in a convex dual formulation. We report thorough experimental results that compare our approach favorably against existing alternatives in both accuracy and efficiency.

关键词： Approximation algorithms

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SEARCH ENGINE CLICK SPAM DETECTION

SEARCH ENGINE CLICK SPAM DETECTION

引用

2012 IEEE 2nd International Conference on Cloud Computing and Intelligence systems

作者： Xin Li Min Zhang Yiqun Liu Shaoping Ma Yijiang Jin Liyun Ru State Key Lab of Intelligent Tech. and Sys Tsinghua National Laboratory for Information Sci. & Tech.Department of Computer Science and TechnologyTsinghua University

Using search engine to retrieve information has become an important part in people's daily life. For most search engines, click information is a significant factor in document ranking. As a result, some websites use cheating methods to get a higher rank by increasing clicks on its page fraudulently in search results to earn huge commercial interest, which is called "Click Spam". Based on the analysis of features of cheating clicks, a novel automatic click spam detection approach is proposed in this paper, which consists of: 1) detect the single click record spam, by which 0.54% of all the clicks are detected as spams;2) model user sessions with a triple sequence which by the first time, to be best of our knowledge, takes not only user action, but also action object and time interval between actions into consideration in related research;3) based on the detected single click record spam and other features, find seed cheating session modes;and then use bipartite graph iterative algorithm to get higher precision and recall of click spam detection. Experiments have been made on Chinese commercial search engine real log data, containing around 80 million user clicks per day. As a result, 2.1% of all the clicks can be detected as spams, and the precision reaches to 97%. The proposed framework is with the high capability to detect click spam precisely and efficiently, which can be easily implemented in real world commercial search engine service.

关键词： Click spam User session Bipartite graph iterative algorithm

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