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ECML
2006
Springer
15 years 3 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
COLT
2008
Springer
15 years 1 months ago
Relating Clustering Stability to Properties of Cluster Boundaries
In this paper, we investigate stability-based methods for cluster model selection, in particular to select the number K of clusters. The scenario under consideration is that clust...
Shai Ben-David, Ulrike von Luxburg
COLT
2008
Springer
15 years 1 months ago
On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms
Boosting algorithms build highly accurate prediction mechanisms from a collection of lowaccuracy predictors. To do so, they employ the notion of weak-learnability. The starting po...
Shai Shalev-Shwartz, Yoram Singer
FAST
2009
14 years 9 months ago
DIADS: Addressing the "My-Problem-or-Yours" Syndrome with Integrated SAN and Database Diagnosis
We present DIADS, an integrated DIAgnosis tool for Databases and Storage area networks (SANs). Existing diagnosis tools in this domain have a database-only (e.g., [11]) or SAN-onl...
Shivnath Babu, Nedyalko Borisov, Sandeep Uttamchan...
ML
2010
ACM
138views Machine Learning» more  ML 2010»
14 years 6 months ago
Mining adversarial patterns via regularized loss minimization
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
Wei Liu, Sanjay Chawla