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ASPLOS
2006
ACM
9 years 7 months ago
Accurate and efficient regression modeling for microarchitectural performance and power prediction
We propose regression modeling as an efficient approach for accurately predicting performance and power for various applications executing on any microprocessor configuration in a...
Benjamin C. Lee, David M. Brooks
IDEAL
2004
Springer
9 years 9 months ago
Orthogonal Least Square with Boosting for Regression
A novel technique is presented to construct sparse regression models based on the orthogonal least square method with boosting. This technique tunes the mean vector and diagonal c...
Sheng Chen, Xunxian Wang, David J. Brown
ECML
2004
Springer
9 years 9 months ago
Inducing Polynomial Equations for Regression
Regression methods aim at inducing models of numeric data. While most state-of-the-art machine learning methods for regression focus on inducing piecewise regression models (regres...
Ljupco Todorovski, Peter Ljubic, Saso Dzeroski
PKDD
2005
Springer
92views Data Mining» more  PKDD 2005»
9 years 9 months ago
Mining Model Trees from Spatial Data
Mining regression models from spatial data is a fundamental task in Spatial Data Mining. We propose a method, namely Mrs-SMOTI, that takes advantage from a tight-integration with s...
Donato Malerba, Michelangelo Ceci, Annalisa Appice
ICSM
2007
IEEE
9 years 10 months ago
On the prediction of the evolution of libre software projects
Libre (free / open source) software development is a complex phenomenon. Many actors (core developers, casual contributors, bug reporters, patch submitters, users, etc.), in many ...
Israel Herraiz, Jesús M. González-Ba...
MLDM
2009
Springer
9 years 10 months ago
Drift-Aware Ensemble Regression
Abstract. Regression models are often required for controlling production processes by predicting parameter values. However, the implicit assumption of standard regression techniqu...
Frank Rosenthal, Peter Benjamin Volk, Martin Hahma...
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