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检索条件"机构=Computer Science and Intelligent Systems Program"
211 条 记 录,以下是151-160 订阅
Preface
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CEUR Workshop Proceedings 2009年 467卷
作者: Cena, Federica Farzan, Rosta Lops, Pasquale Department of Computer Science University of Turin Corso Svizzera 185 10149 Torino Italy Intelligent Systems Program University of Pittsburgh 5108 Sennott Square Building 210 S. Bouquet St. Pittsburgh United States Department of Computer Science University of Bari Via E. Orabona 4 70126 Bari Italy
来源: 评论
Discourse level opinion interpretation
Discourse level opinion interpretation
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22nd International Conference on Computational Linguistics, Coling 2008
作者: Somasundaran, Swapna Wiebe, Janyce Ruppenhofer, Josef Dept. of Computer Science University of Pittsburgh Pittsburgh PA 15260 United States Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States
This work proposes opinion frames as a representation of discourse-level associations which arise from related opinion topics. We illustrate how opinion frames help gather more information and also assist disambiguati... 详细信息
来源: 评论
Discourse level opinion relations: An annotation study  9
Discourse level opinion relations: An annotation study
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9th SIGdial Workshop on Discourse and Dialogue
作者: Somasundaran, Swapna Ruppenhofer, Josef Wiebe, Janyce Dept. of Computer Science University of Pittsburgh Pittsburgh PA 15260 United States Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States
This work proposes opinion frames as a representation of discourse-level associations that arise from related opinion targets and which are common in task-oriented meeting dialogs. We define the opinion frames and exp...
来源: 评论
Insensitivity of constraint-based causal discovery algorithms to violations of the assumption of multivariate normality
Insensitivity of constraint-based causal discovery algorithm...
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21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21
作者: Voortman, Mark Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Faculty of Computer Science Bialystok Technical University Wiejska 45A 15-351 Bialystok Poland
Constraint-based causal discovery algorithms, such as the PC algorithm, rely on conditional independence tests and are otherwise independent of the actual distribution of the data. In case of continuous variables, the... 详细信息
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Argument graph classification via genetic programming and C4.5
Argument graph classification via genetic programming and C4...
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1st International Conference on Educational Data Mining, EDM 2008
作者: Lynch, Collin Ashley, Kevin D. Pinkwart, Niels Aleven, Vincent Intelligent Systems Program University of Pittsburgh United States School of Law University of Pittsburgh United States Department of Informatics Clausthal University of Technology Germany HCII School of Computer Science Carnegie Mellon University United States
In well-defined domains there exist well-accepted criteria for detecting good and bad student solutions. Many ITS implement these criteria characterize solutions and to give immediate feedback. While this has been sho... 详细信息
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The Third International Conference on human-robot interaction
The Third International Conference on human-robot interactio...
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作者: Fong, Terry Dautenhahn, Kerstin Scheutz, Matthias Demiris, Yiannis Intelligent Robotics Group NASA Ames Research Center Department of Artificial Intelligence School of Computer Science University of Herfordshire Herfordshire United Kingdom Adaptive Systems Research Group University of Herfordshire Herfordshire United Kingdom Department of Cognitive Science Computer Science and Informatics Cognitive Science Program Indiana University Bloomington IN United States Intelligent Robotics Team Department of Electrical Engineering Imperial College London London United Kingdom
The third international conference on Human-Robot Interaction (HRI-2008) was held in Amsterdam, The Netherlands, March 12-15, 2008. The theme of HRI-2008, "living with robots," highlights the importance of t... 详细信息
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The impact of overconfidence bias on practical accuracy of Bayesian network models: An empirical study
The impact of overconfidence bias on practical accuracy of B...
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6th UAI Bayesian Modelling Applications Workshop, BMAW 2008
作者: Druzdzel, Marek J. Oniśko, Agnieszka Faculty of Computer Science Bialystok Technical University 15-351 Bialystok Wiejska 45A Poland Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Magee Womens Hospital University of Pittsburgh Medical Center Pittsburgh PA 15260 United States
In this paper, we examine the influence of overconfidence in parameter specification on the performance of a Bayesian network model in the context of Hepar II, a sizeable Bayesian network model for diagnosis of liver ... 详细信息
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Localization of difficult-to-translate phrases  2
Localization of difficult-to-translate phrases
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2nd Workshop on Statistical Machine Translation, WMT 2007 at the 45th Annual Meeting of the Association of Computational Linguistics, ACL 2007
作者: Mohit, Behrang Hwa, Rebecca Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Department of Computer Science University of Pittsburgh PittsburghPA15260 United States
This paper studies the impact that difficult-to-translate source-language phrases might have on the machine translation process. We formulate the notion of difficulty as a measurable quantity;we show that a classifier... 详细信息
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Detecting arguing and sentiment in meetings
Detecting arguing and sentiment in meetings
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8th SIGdial Workshop on Discourseand Dialogue
作者: Somasundaran, Swapna Ruppenhofer, Josef Wiebe, Janyce Dept. of Computer Science University of Pittsburgh Pittsburgh PA 15260 United States Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States
This paper analyzes opinion categories like Sentiment and Arguing in meetings. We first annotate the categories manually. We then develop genre-specific lexicons using interesting function word combinations for detect...
来源: 评论
Generalized evidence pre-propagated importance sampling for hybrid bayesian networks
Generalized evidence pre-propagated importance sampling for ...
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AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
作者: Yuan, Changhe Druzdzel, Marek J. Department of Computer Science and Engineering Mississippi State University Mississippi State MS 39762 Intelligent Systems Program School of Information Sciences University of Pittsburgh Pittsburgh PA 15260
In this paper, we first provide a new theoretical understanding of the Evidence Pre-propagated Importance Sampling algorithm (EPIS-BN) (Yuan & Druzdzel 2003;2006b) and show that its importance function minimizes t... 详细信息
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