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» On Objective Measures of Rule Surprisingness
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CVPR
2001
IEEE
16 years 1 months ago
Learning Models for Object Recognition
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Pedro F. Felzenszwalb
SIAMAM
2011
14 years 6 months ago
Imaging Schemes for Perfectly Conducting Cracks
We consider the problem of locating perfectly conducting cracks and estimating their geometric features from multi-static response matrix measurements at a single or multiple frequ...
Habib Ammari, Josselin Garnier, Hyeonbae Kang, Won...
ICALP
2009
Springer
15 years 6 months ago
Improved Bounds for Speed Scaling in Devices Obeying the Cube-Root Rule
Speed scaling is a power management technique that involves dynamically changing the speed of a processor. This gives rise to dualobjective scheduling problems, where the operating...
Nikhil Bansal, Ho-Leung Chan, Kirk Pruhs, Dmitriy ...
ER
1997
Springer
148views Database» more  ER 1997»
15 years 3 months ago
Intelligent Support for Retrieval and Synthesis of Patterns for Object-Oriented Design
Several decades of software engineering research confirm that effective reuse is the only realistic approach to meeting the ever-increasing demands on the software industry. Over ...
Sandeep Purao, Veda C. Storey
107
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ICTAI
2007
IEEE
15 years 6 months ago
Exploratory Quantitative Contrast Set Mining: A Discretization Approach
Contrast sets have been shown to be a useful tool for describing differences between groups. A contrast set is a set of association rules for which the antecedents describe distin...
Mondelle Simeon, Robert J. Hilderman