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Solving factored MDPs with exponential-family transition models

Solving factored MDPs with exponential-family transition mod...

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ICAPS 2006 - 16th International Conference on Automated Planning and Scheduling

作者： Kveton, Branislav Hauskrecht, Milos Intelligent Systems Program University of Pittsburgh Department of Computer Science University of Pittsburgh

Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALF). The main idea of the approach is to approximate the optimal value function by a linear combination of basis functions and optimize it by linear programming. In this paper, we extend the existing HALP paradigm beyond the mixture of beta transition model. As a consequence, we permit other transition functions, such as normals, without approximating them. Moreover, we identify a large class of basis functions that match these transition models and yield an efficient solution to the expectation terms in HALP. Finally, we apply the generalized HALP framework to solve a rover planning problem, which involves continuous time and resource uncertainty. Copyright © 2006, American Association for Artificial Intelligence (***). All rights reserved.

关键词： Decision making

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Manual Annotation of Opinion Categories in Meetings 7

Manual Annotation of Opinion Categories in Meetings

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7th International Workshop on Linguistically Interpreted Corpora, LINC-2006 and 3rd Frontiers in Corpus Annotation

作者： Somasundaran, Swapna Wiebe, Janyce Hoffmann, Paul Litman, Diane Department of Computer Science University of Pittsburgh PittsburghPA15260 United States Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States

ISBN: (纸本)1932432787

This paper applies the categories from an opinion annotation scheme developed for monologue text to the genre of multiparty meetings. We describe modifications to the coding guidelines that were required to extend the categories to the new type of data, and present the results of an inter-annotator agreement study. As researchers have found with other types of annotations in speech data, interannotator agreement is higher when the annotators both read and listen to the data than when they only read the transcripts. Previous work exploited prosodic clues to perform automatic detection of speaker emotion (Liscombe et al. 2003). Our findings suggest that doing so to recognize opinion categories would be a promising line of work. © 2006 Association for Computational Linguistics.

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Which side are you on? Identifying perspectives at the document and sentence levels 10

Which side are you on? Identifying perspectives at the docum...

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10th Conference on Computational Natural Language Learning, CoNLL-X

作者： Lin, Wei-Hao Wilson, Theresa Wiebe, Janyce Hauptmann, Alexander Language Technologies Institute Carnegie Mellon University Pittsburgh PA 15213 United States Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 United States

In this paper we investigate a new problem of identifying the perspective from which a document is written. By perspective we mean a point of view, for example, from the perspective of Democrats or Republicans. Can computers learn to identify the perspective of a document? Not every sentence is written strongly from a perspective. Can computers learn to identify which sentences strongly convey a particular perspective? We develop statistical models to capture how perspectives are expressed at the document and sentence levels, and evaluate the proposed models on articles about the Israeli-Palestinian conflict. The results show that the proposed models successfully learn how perspectives are reflected in word usage and can identify the perspective of a document with high accuracy. ©2006 Association for Computational Linguistics.

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Wood Defect Detection using Grayscale Images and an Optimized Feature Set

Wood Defect Detection using Grayscale Images and an Optimize...

引用

Annual Conference of Industrial Electronics Society

作者： P. Cavalin L. S. Oliveira A. L. Koerich A. S. Britto INVISYS Intelligent Vision Systems Curitiba Brazil Graduate Program in Computer Science Pontifical Catholic University of Paraná Curitiba Brazil

In this paper we address the issue of detecting defects in wood using features extracted from grayscale images. The feature set proposed here is based on the concept of texture and it is computed from the co-occurrence matrices. The features provide measures of properties such as smoothness, coarseness, and regularity. Comparative experiments using a color image based feature set extracted from percentile histograms are carried to demonstrate the efficiency of the proposed feature set. Two different learning paradigms, neural networks and support vector machines, and a feature selection algorithm based on multi-objective genetic algorithms were considered in our experiments. The experimental results show that after feature selection, the grayscale image based feature set achieves very competitive performance for the problem of wood defect detection relative to the color image based features

关键词： Gray-scale Histograms Feature extraction Color Machine learning Neural networks Support vector machines Genetic algorithms Humans Robustness

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Wood defect detection using grayscale images and an optimized feature set

Wood defect detection using grayscale images and an optimize...

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IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics

作者： Cavalin, P. Oliveira, L.S. Koerich, A.L. Britto Jr., A.S. Pontifical Catholic University of Parana Graduate Program in Computer Science Rua Imaculada Conceição 1155 Curitiba PR 80215-901 Brazil INVISYS Intelligent Vision Systems Rua Prof. Algacyr Munhoz Mader 3775 Curitiba PR 80350-010 Brazil

ISBN: (纸本)1424401364

关键词： Feature Selection

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Building an English-Iraqi Arabic machine translation system for spoken utterances with limited resources

Building an English-Iraqi Arabic machine translation system ...

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INTERSPEECH 2006 and 9th International Conference on Spoken Language Processing, INTERSPEECH 2006 - ICSLP

作者： Riesa, Jason Mohit, Behrang Knight, Kevin Marcu, Daniel Department of Computer Science Johns Hopkins University Baltimore MD 21218 United States Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Information Sciences Institute University of Southern California Marina del Rey CA 90292 United States

ISBN: (纸本)9781604234497

This paper presents an English-Iraqi Arabic speech-to-speech statistical machine translation system using limited resources. In it, we explore the constraints involved, how we endeavored to mitigate such problems as a non-standard orthography and a highly inflected grammar, and discuss leveraging existing plentiful resources for Modern Standard Arabic to assist in this task. These combined techniques yield a reduction in unknown words at translation time by over 40% and a +3.65 increase in BLEU score over a previous state-of-the-art system using the same parallel training corpus of spoken utterances.

关键词： computer aided language translation

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Using system and user performance features to improve emotion detection in spoken tutoring dialogs

Using system and user performance features to improve emotio...

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INTERSPEECH 2006 and 9th International Conference on Spoken Language Processing, INTERSPEECH 2006 - ICSLP

作者： Hua, Ai Litman, Diane J. Forbes-Riley, Kate Rotaru, Mihai Tetreault, Joel Purandare, Amruta Intelligent Systems Program University of Pittsburgh 210 S. Bouquet Pittsburgh PA 15260 United States Learning Research and Development Center University of Pittsburgh 210 S. Bouquet Pittsburgh PA 15260 United States Dept. of Computer Science University of Pittsburgh 210 S. Bouquet Pittsburgh PA 15260 United States

ISBN: (纸本)9781604234497

In this study, we incorporate automatically obtained system/user performance features into machine learning experiments to detect student emotion in computer tutoring dialogs. Our results show a relative improvement of 2.7% on classification accuracy and 8.08% on Kappa over using standard lexical, prosodie, sequential, and identification features. This level of improvement is comparable to the performance improvement shown in previous studies by applying dialog acts or lexical/prosodic-/discourse- level contextual features.

关键词： Emotion Recognition

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ISHM implementation for Constellation systems

ISHM implementation for Constellation Systems

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AIAA/ASME/SAE/ASEE 42nd Joint Propulsion Conference

作者： Figueroa, Fernando Holland, Randy Schmalzel, John Duncavage, Dan Crocker, Alan Alena, Rick NASA Stennis Space Center Stennis Space Center MS 39529 Rowan University Dept. of Electrical and Computer Engineering Glassboro NJ 08028 NASA Johnson Space Center Houston TX 77058 NASA Ames Research Center Moffett Field CA 94035 Science and Technology Division EA41 Stennis Space Center MS 39529 AIAA Department of Electrical and Computer Engineering Rowan University Glassboro NJ 08028 International Space Station Program OD NASA Johnson Space Center Houston TX 77058 Systems Division Mission Operations Directorate DF NASA Johnson Space Center Houston TX 77058 Intelligent Systems Division MS 269-4 Moffett Field CA 94035

ISBN: (纸本)1563478188

This paper addresses methodic implementation of a credible ISHM capability for elements of Constellation systems. ISHM capability must be implemented by a combination of on-board and ground elements, each contributing to determining the health of systems in the most effective manner. Implementation of ISHM capability must evolve continuously to reach higher and higher levels of functional capability. The implication is that a sustainable approach must be defined in order to accomplish a believable capability. This paper describes the methodology, the elements, and the technology to implement ISHM capability throughout the life cycle of elements of Constellation systems, reaching beyond individual elements that might have a limited life while the constellation moves on.

关键词： Spacecraft propulsion

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Syntax-based semi-supervised named entity tagging 05

Syntax-based semi-supervised named entity tagging

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43rd Annual Meeting of the Association for Computational Linguistics, ACL-05

作者： Mohit, Behrang Hwa, Rebecca Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Computer Science Department University of Pittsburgh Pittsburgh PA 15260 United States

ISBN: (纸本)1932432515

We report an empirical study on the role of syntactic features in building a semisupervised named entity (NE) tagger. Our study addresses two questions: What types of syntactic features are suitable for extracting potential NEs to train a classifier in a semi-supervised setting? How good is the resulting NE classifier on testing instances dissimilar from its training data? Our study shows that constituency and dependency parsing constraints are both suitable features to extract NEs and train the classifier. Moreover, the classifier showed significant accuracy improvement when constituency features are combined with new dependency feature. Furthermore, the degradation in accuracy on unfamiliar test cases is low, suggesting that the trained classifier generalizes well. © 2005 Association for Computational Linguistics.

关键词： Syntactics

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Recognizing contextual polarity in phrase-level sentiment analysis 05

Recognizing contextual polarity in phrase-level sentiment an...

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Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, HLT/EMNLP 2005, Co-located with the 2005 Document Understanding Conference, DUC and the 9th International Workshop on Parsing Technologies, IWPT

作者： Wilson, Theresa Wiebe, Janyce Hoffmann, Paul Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Department of Computer Science University of Pittsburgh Pittsburgh PA 15260 United States

This paper presents a new approach to phrase-level sentiment analysis that first determines whether an expression is neutral or polar and then disambiguates the polarity of the polar expressions. With this approach, the system is able to automatically identify the contextual polarity for a large subset of sentiment expressions, achieving results that are significantly better than baseline. © 2005 Association for Computational Linguistics.

关键词： Sentiment analysis

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