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» A Kernel Approach to Comparing Distributions
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CIKM
2008
Springer
14 years 11 months ago
Classifying networked entities with modularity kernels
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
Dell Zhang, Robert Mao
CVPR
2010
IEEE
14 years 10 months ago
Learning kernels for variants of normalized cuts: Convex relaxations and applications
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
Lopamudra Mukherjee, Vikas Singh, Jiming Peng, Chr...
JMLR
2006
136views more  JMLR 2006»
14 years 9 months ago
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
Tonatiuh Peña Centeno, Neil D. Lawrence
ECML
2006
Springer
15 years 1 months ago
Sequence Discrimination Using Phase-Type Distributions
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Jérôme Callut, Pierre Dupont
DAGM
2011
Springer
13 years 9 months ago
Relaxed Exponential Kernels for Unsupervised Learning
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...