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» A Kernel Between Sets of Vectors
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KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 9 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
COLT
2003
Springer
14 years 2 months ago
Learning from Uncertain Data
The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ï¬...
Mehryar Mohri
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
14 years 1 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
NIPS
2001
13 years 10 months ago
K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms
Guided by an initial idea of building a complex (non linear) decision surface with maximal local margin in input space, we give a possible geometrical intuition as to why K-Neares...
Pascal Vincent, Yoshua Bengio
FSTTCS
2010
Springer
13 years 6 months ago
Place-Boundedness for Vector Addition Systems with one zero-test
Reachability and boundedness problems have been shown decidable for Vector Addition Systems with one zero-test. Surprisingly, place-boundedness remained open. We provide here a va...
Rémi Bonnet, Alain Finkel, Jérô...