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» Selection of Subsets of Ordered Features in Machine Learning
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ECML
2007
Springer
15 years 10 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
JMLR
2010
187views more  JMLR 2010»
14 years 10 months ago
SFO: A Toolbox for Submodular Function Optimization
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
Andreas Krause
125
Voted
ICPR
2008
IEEE
16 years 5 months ago
Multiple classifier applied on predicting microsleep from speech
The aim of this study is to apply a state-of-the-art speech emotion recognition engine on the detection of microsleep endangered sleepiness states. Current approaches in speech em...
Jarek Krajewski, Anton Batliner, Rainer Wieland
CGO
2007
IEEE
15 years 10 months ago
Rapidly Selecting Good Compiler Optimizations using Performance Counters
Applying the right compiler optimizations to a particular program can have a significant impact on program performance. Due to the non-linear interaction of compiler optimization...
John Cavazos, Grigori Fursin, Felix V. Agakov, Edw...
136
Voted
PRL
2007
100views more  PRL 2007»
15 years 3 months ago
Visible models for interactive pattern recognition
The bottleneck in interactive visual classification is the exchange of information between human and machine. We introduce the concept of the visible model, which is an ion of an ...
Jie Zou, George Nagy