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MLDM
2005
Springer
14 years 3 months ago
Using Clustering to Learn Distance Functions for Supervised Similarity Assessment
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 3 months ago
On the appropriateness of evolutionary rule learning algorithms for malware detection
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classi...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
ALT
2001
Springer
14 years 7 months ago
Learning How to Separate
The main question addressed in the present work is how to find effectively a recursive function separating two sets drawn arbitrarily from a given collection of disjoint sets. I...
Sanjay Jain, Frank Stephan
OSDI
2008
ACM
14 years 10 months ago
Hunting for Problems with Artemis
Artemis is a modular application designed for analyzing and troubleshooting the performance of large clusters running datacenter services. Artemis is composed of four modules: (1)...
Gabriela F. Cretu-Ciocarlie, Mihai Budiu, Mois&eac...
COLT
2001
Springer
14 years 2 months ago
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
Peter L. Bartlett, Shahar Mendelson