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» Selecting Robust Strategies Based on Abstracted Game Models
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ML
2010
ACM
127views Machine Learning» more  ML 2010»
15 years 10 days ago
Stability and model selection in k-means clustering
Abstract Clustering Stability methods are a family of widely used model selection techniques for data clustering. Their unifying theme is that an appropriate model should result in...
Ohad Shamir, Naftali Tishby
ISDA
2010
IEEE
14 years 11 months ago
Avoiding simplification strategies by introducing multi-objectiveness in real world problems
Abstract--In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-m...
Charlotte J. C. Rietveld, Gijs P. Hendrix, Frank T...
ICRA
2009
IEEE
106views Robotics» more  ICRA 2009»
15 years 8 months ago
Stochastic strategies for a swarm robotic assembly system
— We present a decentralized, scalable approach to assembling a group of heterogeneous parts into different products using a swarm of robots. While the assembly plans are predete...
Loic Matthey, Spring Berman, Vijay Kumar
SIGIR
2006
ACM
15 years 7 months ago
Feature diversity in cluster ensembles for robust document clustering
The performance of document clustering systems depends on employing optimal text representations, which are not only difficult to determine beforehand, but also may vary from one ...
Xavier Sevillano, Germán Cobo, Francesc Al&...
CBMS
2008
IEEE
15 years 3 months ago
Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may ...
Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal