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» The Linux Kernel Configurator as a Feature Modeling Tool
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EMMCVPR
2009
Springer
14 years 2 months ago
Clustering-Based Construction of Hidden Markov Models for Generative Kernels
Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the fi...
Manuele Bicego, Marco Cristani, Vittorio Murino, E...
ESANN
2006
13 years 9 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
ICS
2009
Tsinghua U.
14 years 2 months ago
High-performance CUDA kernel execution on FPGAs
In this work, we propose a new FPGA design flow that combines the CUDA programming model from Nvidia with the state of the art high-level synthesis tool AutoPilot from AutoESL, to...
Alexandros Papakonstantinou, Karthik Gururaj, John...
LREC
2010
159views Education» more  LREC 2010»
13 years 9 months ago
Improvements in Parsing the Index Thomisticus Treebank. Revision, Combination and a Feature Model for Medieval Latin
The creation of language resources for less-resourced languages like the historical ones benefits from the exploitation of language-independent tools and methods developed over th...
Marco Passarotti, Felice dell'Orletta
SPLC
2010
13 years 6 months ago
Stratified Analytic Hierarchy Process: Prioritization and Selection of Software Features
Product line engineering allows for the rapid development of variants of a domain specific application by using a common set of reusable assets often known as core assets. Variabil...
Ebrahim Bagheri, Mohsen Asadi, Dragan Gasevic, Sam...