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检索条件"机构=Computer Science and Intelligent Systems Program"
214 条 记 录,以下是161-170 订阅
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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...
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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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Importance sampling for general hybrid Bayesian networks
Importance sampling for general hybrid Bayesian networks
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11th International Conference on Artificial Intelligence and Statistics, AISTATS 2007
作者: Yuan, Changhe Druzdzel, Marek J. Department of Computer Science and Engineering Mississippi State University Mississippi State MS 39762 United States Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States
Some real problems are more naturally modeled by hybrid Bayesian networks that consist of mixtures of continuous and discrete variables with their interactions described by equations and continuous probability distrib... 详细信息
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Implementing and Improving a method for non-invasive elicitation of probabilities for bayesian networks  07
Implementing and Improving a method for non-invasive elicita...
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International Conference on computer systems and Technologies and Workshop for PhD Students in Computing, CompSysTech '07
作者: De Jongh, Martinus Druzdzel, Marek Rothkrantz, Leon Faculty of Electrical Engineering Mathematics and Computer Science Man-Machine Interaction Group Delft University of Technology Delft Netherlands Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA United States
Knowledge elicitation is difficult for expert systems that are based on probability theory. The elicitation of probabilities for a probabilistic model requires a lot of time and interaction between the knowledge engin... 详细信息
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ASSIST: Adaptive social support for information space traversal  07
ASSIST: Adaptive social support for information space traver...
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Hypertext 2007: 18th ACM Conference on Hypertext and Hypermedia, HT'07
作者: Farzan, Rosta Coyle, Maurice Freyne, Jill Brusilovsky, Peter Smyth, Barry University of Pittsburgh Intelligent Systems Program Pittsburgh PA 15260 United States University College Dublin School of Computer Science and Informatics Belfield Dublin 4 Ireland University of Pittsburgh School of Information Science Pittsburgh PA 15260 United States
Finding relevant information in a hyperspace has been a much studied problem for many years. With the emergence of so called Web 2.0 technologies we have seen the use of social systems for retrieval tasks increasing d... 详细信息
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Comparing user simulation models for dialog strategy learning
Comparing user simulation models for dialog strategy learnin...
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2007 Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, NAACL-HLT 2007
作者: Ai, Hua Tetreault, Joel R. Litman, Diane J. University of Pittsburgh Intelligent Systems Program PittsburghPA15260 United States University of Pittsburgh LRDC PittsburghPA15260 United States University of Pittsburgh Dept. of Computer Science LRDC PittsburghPA15260 United States
This paper explores what kind of user simulation model is suitable for developing a training corpus for using Markov Decision Processes (MDPs) to automatically learn dialog strategies. Our results suggest that with sp... 详细信息
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Learning by diagramming Supreme Court oral arguments  07
Learning by diagramming Supreme Court oral arguments
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11th International Conference on Artificial Intelligence and Law
作者: Ashley, Kevin Pinkwart, Niels Lynch, Collin Aleven, Vincent LRDC School of Law University of Pittsburgh Pittsburgh PA United States Computer Science Institute Clausthal University of Technology Germany Intelligent Systems Program University of Pittsburgh Pittsburgh PA United States Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States
This paper describes an intelligent tutoring system, LARGO, that helps students learn skills of legal reasoning with hypotheticals by analyzing oral arguments before the US Supreme Court. The skills involve proposing ... 详细信息
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Comparing spoken dialog corpora collected with recruited subjects versus real users
Comparing spoken dialog corpora collected with recruited sub...
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8th SIGdial Workshop on Discourseand Dialogue
作者: Ai, Hua Raux, Antoine Bohus, Dan Eskenazi, Maxine Litman, Diane Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Language Technologies Institute Carnegie Mellon University Pittsburgh PA 15213 United States Computer Science Department Carnegie Mellon University Pittsburgh PA 15213 United States Dept. of Computer Science LRDC University of Pittsburgh Pittsburgh PA 15260 United States Microsoft Research Redmond WA United States
Empirical spoken dialog research often involves the collection and analysis of a dialog corpus. However, it is not well understood whether and how a corpus of dialogs collected using recruited subjects differs from a ...
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Approximate linear programming for solving hybrid factored MDPs
Approximate linear programming for solving hybrid factored M...
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9th International Symposium on Artificial Intelligence and Mathematics, ISAIM 2006
作者: Hauskrecht, Milos Kveton, Branislav Department of Computer Science Intelligent Systems Program University of Pittsburgh United States
Hybrid approximate linear programming (HALP) has recently emerged as a promising approach to solving large factored Markov decision processes (MDPs) with discrete and continuous state and action variables. Its central... 详细信息
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Learning basis functions in hybrid domains
Learning basis functions in hybrid domains
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21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
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 ... 详细信息
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