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A. Monsifrot and F. Bodin. A machine learning approach to automatic production of compiler heuristics. In Tenth International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), pages 41--50, Varna, Bulgaria, September 2002. Springer Verlag.

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This paper is cited in the following contexts:
Meta Optimization: Improving Compiler Heuristics.. - Stephenson.. (2002)   (5 citations)  (Correct)

....of our learning techniques. They use misprediction rates to guide the learning process. While this is a perfectly valid choice, it does not necessarily reflect the bottom line: execution time. Monsifrot et al. use a classifier based on decision tree learning to determine which loops to unroll [17]. Like [5] this supervised methodology relies on extracting labels, which is not only di#cult, in many cases it is simply not feasible. Cooper et al. use genetic algorithms to solve compilation phase ordering problems [8] Their technique is quite effective. However, like other related work, ....

A. Monsifrot, F. Bodin, and R. Quiniou. A Machine Learning Approach to Automatic Production of Compiler Heuristics. In Artificial Intelligence: Methodology, Systems, Applications, pages 41--50, 2002.


Method-Specific Dynamic Compilation using Logistic Regression - John Cavazos Michael   (Correct)

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A. Monsifrot and F. Bodin. A machine learning approach to automatic production of compiler heuristics. In Tenth International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), pages 41--50, Varna, Bulgaria, September 2002. Springer Verlag.


Inducing Heuristics To Decide Whether To Schedule - John Cavazos University   (Correct)

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A. Monsifrot and F. Bodin. A machine learning approach to automatic production of compiler heuristics. In Tenth International Conference on Artificial Intelligence: Methodology, Systems, Applications, AIMSA, pages 41--50, September 2002.


Hybrid Optimizations: - Which Optimization Algorithm   (Correct)

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A. Monsifrot and F. Bodin. A machine learning approach to automatic production of compiler heuristics. In Tenth International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), pages 41--50, Varna, Bulgaria, September 2002. Springer Verlag.


Automatic Tuning of Inlining Heuristics - John Cavazos Michael   (Correct)

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A. Monsifrot and F. Bodin. A machine learning approach to automatic production of compiler heuristics. In Tenth International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), pages 41--50, Varna, Bulgaria, September 2002. Springer Verlag.


A Practical Method for Quickly Evaluating Program.. - Fursin, Cohen, O'Boyle.. (2005)   (Correct)

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A. Monsifrot, F. Bodin, and R. Quiniou. A machine learning approach to automatic production of compiler heuristics. In Proc. AIMSA, LNCS 2443, pages 41--50, 2002.


A Practical Method for Quickly Evaluating Program.. - Fursin, Cohen, O'Boyle.. (2005)   (Correct)

No context found.

A. Monsifrot, F. Bodin, and R. Quiniou. A machine learning approach to automatic production of compiler heuristics. In Proc. AIMSA, LNCS 2443, pages 41--50, 2002.


Adaptive Java Optimisation Using Instance-Based Learning - Long, O'Boyle (2004)   (1 citation)  (Correct)

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A. Monsifrot, F. Bodin and R. Quiniou. A machine learning approach to automatic production of compiler heuristics. The 10th International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), 2002.

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