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MICRO
2009
IEEE
113views Hardware» more  MICRO 2009»
14 years 3 months ago
Portable compiler optimisation across embedded programs and microarchitectures using machine learning
Building an optimising compiler is a difficult and time consuming task which must be repeated for each generation of a microprocessor. As the underlying microarchitecture changes...
Christophe Dubach, Timothy M. Jones, Edwin V. Boni...
AAI
2008
93views more  AAI 2008»
13 years 9 months ago
Adaptive Machine Learning in Delayed Feedback Domains by Selective Relearning
We present a novel hybrid technique for improving the predictive performance of an online Machine Learning system: Combining advantages from both memory based and concept based pr...
Marcus-Christopher Ludl, Achim Lewandowski, Georg ...
INTERSPEECH
2010
13 years 3 months ago
Using dependency parsing and machine learning for factoid question answering on spoken documents
This paper presents our experiments in question answering for speech corpora. These experiments focus on improving the answer extraction step of the QA process. We present two app...
Pere Comas, Jordi Turmo, Lluís Màrqu...
TNN
2010
159views Management» more  TNN 2010»
13 years 3 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
AUTOMATICA
2006
150views more  AUTOMATICA 2006»
13 years 8 months ago
Enlarging the terminal region of nonlinear model predictive control using the support vector machine method
In this paper, Receding Horizon Model Predictive Control (RHMPC) of nonlinear systems subject to input and state constraints is considered. We propose to estimate the terminal reg...
Chong Jin Ong, Dan Sui, Elmer G. Gilbert