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ICML
2006
IEEE
16 years 6 months ago
Nightmare at test time: robust learning by feature deletion
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
Amir Globerson, Sam T. Roweis
ICML
2004
IEEE
16 years 6 months ago
Robust feature induction for support vector machines
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...
Rong Jin, Huan Liu
152
Voted
CGO
2009
IEEE
15 years 12 months ago
Automatic Feature Generation for Machine Learning Based Optimizing Compilation
Recent work has shown that machine learning can automate and in some cases outperform hand crafted compiler optimizations. Central to such an approach is that machine learning tec...
Hugh Leather, Edwin V. Bonilla, Michael O'Boyle
IROS
2007
IEEE
158views Robotics» more  IROS 2007»
15 years 11 months ago
Feature selection in conditional random fields for activity recognition
Abstract— Temporal classification, such as activity recognition, is a key component for creating intelligent robot systems. In the case of robots, classification algorithms mus...
Douglas L. Vail, John D. Lafferty, Manuela M. Velo...
RE
2009
Springer
15 years 9 months ago
A Use Case Based Approach to Feature Models' Construction
In the research of software reuse, feature models have been widely adopted to organize the requirements of a set of applications in a software domain. However, there still lacks a...
Bo Wang, Wei Zhang, Haiyan Zhao, Zhi Jin, Hong Mei