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TKDE
2012
245views Formal Methods» more  TKDE 2012»
13 years 3 days ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung
MA
2010
Springer
168views Communications» more  MA 2010»
14 years 8 months ago
Bounds for the sum of dependent risks having overlapping marginals
We describe several analytical and numerical procedures to obtain bounds on the distribution function of a sum of n dependent risks having fixed overlapping marginals. As an appl...
Paul Embrechts, Giovanni Puccetti
COLT
2001
Springer
15 years 2 months ago
Limitations of Learning via Embeddings in Euclidean Half-Spaces
The notion of embedding a class of dichotomies in a class of linear half spaces is central to the support vector machines paradigm. We examine the question of determining the mini...
Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon
JMLR
2012
13 years 5 days ago
Maximum Margin Temporal Clustering
Temporal Clustering (TC) refers to the factorization of multiple time series into a set of non-overlapping segments that belong to k temporal clusters. Existing methods based on e...
Minh Hoai Nguyen, Fernando De la Torre
NIPS
2007
14 years 11 months ago
Boosting Algorithms for Maximizing the Soft Margin
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...