Aysha Akther, Heung-Nam Kim, Majdi Rawashdeh, Abdulmotaleb's Advances in Artificial Intelligence: 25th Canadian PDF

By Aysha Akther, Heung-Nam Kim, Majdi Rawashdeh, Abdulmotaleb El Saddik (auth.), Leila Kosseim, Diana Inkpen (eds.)

ISBN-10: 3642303536

ISBN-13: 9783642303531

This ebook constitutes the refereed complaints of the twenty fifth Canadian convention on man made Intelligence, Canadian AI 2012, held in Toronto, Canada, in could 2012. The 23 typical papers, sixteen brief papers, and four papers from the Graduate pupil Symposium awarded have been rigorously reviewed and chosen for inclusion during this publication. The papers hide a extensive variety of issues providing unique paintings in all parts of man-made intelligence, both theoretical or applied.

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Additional resources for Advances in Artificial Intelligence: 25th Canadian Conference on Artificial Intelligence, Canadian AI 2012, Toronto, ON, Canada, May 28-30, 2012. Proceedings

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Timeout and Overhead Handling. , DIR, BOA, and PERF), we set the cut-off CPU time to one hour and use that value as the recorded run-time of timed-out instances. For ParamILS learning, the time to generate a macro set for a given cluster of instances was varied depending on the number of initial macros and the difficulty of the original domain. For most experiments the cut-off time was one or two hours. , the mystery-VHPOP-MANUAL cut-off was four hours). Online, one CPU hour is given to solve each test instance.

1398, pp. 160–171. Springer, Heidelberg (1998) 22. : Efficient Pairwise Classification. , Skowron, A. ) ECML 2007. LNCS (LNAI), vol. 4701, pp. 658–665. Springer, Heidelberg (2007) 23. : Large margin dags for multiclass classification. Advances in Neural Information Processing Systems 12, 547–553 (2000) 24. : Empirical analysis of support vector machine ensemble classifiers. Expert Systems with Applications 36(3, Part 2), 6466–6476 (2009) 25. : Binary labelling and decision-level fusion. Information Fusion 2(2), 103–112 (2001) 26.

Hardware and Software Details. The experiments were conducted on a Beowulf cluster with each node consisting of two Dual Core AMD 270 CPUs, 4 GB of main memory, and 80 GB of disk space. All nodes run Red Hat Enterprise Linux. 3 We used Ruby to write all the code. Table 2. page=macroff. ca/labs/beta/Projects/ParamILS/ on 28 Oct. 2009. 2 M. C. Beck Experiment 1: Fixed Macro Set Learning In this experiment, we compare the performance of the best fixed-macro-set found by ParamILS to that produced by Wizard and Macro-FF.

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Advances in Artificial Intelligence: 25th Canadian Conference on Artificial Intelligence, Canadian AI 2012, Toronto, ON, Canada, May 28-30, 2012. Proceedings by Aysha Akther, Heung-Nam Kim, Majdi Rawashdeh, Abdulmotaleb El Saddik (auth.), Leila Kosseim, Diana Inkpen (eds.)


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