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ICML
2006
IEEE
16 years 3 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
VAMOS
2007
Springer
15 years 8 months ago
FAMA: Tooling a Framework for the Automated Analysis of Feature Models
The automated analysis of feature models is recognized as one of the key challenges for automated software development in the context of Software Product Lines (SPL). However, aft...
David Benavides, Sergio Segura, Pablo Trinidad, An...
EWCBR
2004
Springer
15 years 7 months ago
Learning Feature Taxonomies for Case Indexing
Taxonomic case retrieval systems significantly outperform standard conversational case retrieval systems. However, their feature taxonomies, which are the principal reason for thei...
Kalyan Moy Gupta, David W. Aha, Philip G. Moore
FIW
1998
130views Communications» more  FIW 1998»
15 years 3 months ago
A Heuristic Approach to Detect Feature Interactions in Requirements
We present a method to systematically detect feature interactions in requirements, which are expressed as constraints on system event traces. We show its application on the lift sy...
Maritta Heisel, Jeanine Souquières
123
Voted
BCS
2008
15 years 3 months ago
On Using Physical Analogies for Feature and Shape Extraction in Computer Vision
: There is a rich literature of approaches to image feature extraction in computer vision. Many sophisticated approaches exist for low- and high-level feature extraction but can be...
Mark S. Nixon, Cem Direkoglu, Xin U. Liu, David J....