Decision tree model

Results: 142



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21Decision Procedures for Algebraic Data Types with Abstractions

Decision Procedures for Algebraic Data Types with Abstractions

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Source URL: lara.epfl.ch

Language: English - Date: 2009-11-10 09:06:44
22An Efficient Decision Procedure for Imperative Tree Data Structures ? Thomas Wies1 , Marco Mu˜niz2 , and Viktor Kuncak3 1  Institute of Science and Technology (IST), Austria

An Efficient Decision Procedure for Imperative Tree Data Structures ? Thomas Wies1 , Marco Mu˜niz2 , and Viktor Kuncak3 1 Institute of Science and Technology (IST), Austria

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Source URL: lara.epfl.ch

Language: English - Date: 2011-05-02 03:09:28
23Decision Procedures for CTL∗ Oliver Friedmann and Markus Latte Dept. of Computer Science, University of Munich, Germany Abstract. We give an overview over three serious attempts to devise an effective decision method

Decision Procedures for CTL∗ Oliver Friedmann and Markus Latte Dept. of Computer Science, University of Munich, Germany Abstract. We give an overview over three serious attempts to devise an effective decision method

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Source URL: files.oliverfriedmann.de

Language: English - Date: 2012-02-10 07:43:07
24Using Relevance Queries for Identification of Read-Once Functions

Using Relevance Queries for Identification of Read-Once Functions

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Source URL: www.mpi-sws.org

Language: English - Date: 2013-02-16 12:55:16
25Algorithms  Lecture 28: Lower Bounds [Fa’13] It was a Game called Yes and No, where Scrooge’s nephew had to think of something, and the rest must find out what; he only answering to their questions yes or no, as the

Algorithms Lecture 28: Lower Bounds [Fa’13] It was a Game called Yes and No, where Scrooge’s nephew had to think of something, and the rest must find out what; he only answering to their questions yes or no, as the

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Source URL: web.engr.illinois.edu

Language: English - Date: 2014-12-28 09:03:15
26Efficient Noise-Tolerant Learning from Statistical Queries MICHAEL KEARNS AT&T Laboratories—Research, Florham Park, New Jersey  Abstract. In this paper, we study the problem of learning in the presence of classificatio

Efficient Noise-Tolerant Learning from Statistical Queries MICHAEL KEARNS AT&T Laboratories—Research, Florham Park, New Jersey Abstract. In this paper, we study the problem of learning in the presence of classificatio

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Source URL: www.cs.iastate.edu

Language: English - Date: 2003-04-11 14:26:30
27Box-Trees and R-trees with Near-Optimal Query Time P. K. Agarwaly , M. de Bergz , J. Gudmundssonz, M. Hammarx , H. J. Haverkortz y Dept. of Computer Science, Box 90129, Duke University, Durham, NC, USA, panka

Box-Trees and R-trees with Near-Optimal Query Time P. K. Agarwaly , M. de Bergz , J. Gudmundssonz, M. Hammarx , H. J. Haverkortz y Dept. of Computer Science, Box 90129, Duke University, Durham, NC, USA, panka

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Source URL: webdoc.sub.gwdg.de

Language: English - Date: 2006-04-25 01:39:06
28Vol. 377: 1–11, 2009 doi: meps07839 MARINE ECOLOGY PROGRESS SERIES Mar Ecol Prog Ser

Vol. 377: 1–11, 2009 doi: meps07839 MARINE ECOLOGY PROGRESS SERIES Mar Ecol Prog Ser

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Source URL: www.int-res.com

Language: English
29➠  ➡ Refining Segmental Boundaries for TTS Database Using Fine ContextualDependent Boundary Models Lijuan Wang1, Yong Zhao2, Min Chu2, Jianlai Zhou2 and Zhigang Cao1 1

➠ ➡ Refining Segmental Boundaries for TTS Database Using Fine ContextualDependent Boundary Models Lijuan Wang1, Yong Zhao2, Min Chu2, Jianlai Zhou2 and Zhigang Cao1 1

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Source URL: research.microsoft.com

Language: English - Date: 2009-08-10 10:41:28