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» On the generalization of soft margin algorithms
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ICCV
1999
IEEE
14 years 9 months ago
Control in a 3D Reconstruction System using Selective Perception
This paper presents a control structure for general purpose image understanding that addresses both the high level of uncertainty in local hypotheses and the computational complex...
Maurício Marengoni, Allen R. Hanson, Shlomo...
GECCO
2007
Springer
215views Optimization» more  GECCO 2007»
14 years 2 months ago
Addressing sampling errors and diversity loss in UMDA
Estimation of distribution algorithms replace the typical crossover and mutation operators by constructing a probabilistic model and generating offspring according to this model....
Jürgen Branke, Clemens Lode, Jonathan L. Shap...
ISSAC
2005
Springer
105views Mathematics» more  ISSAC 2005»
14 years 1 months ago
Computing the rank and a small nullspace basis of a polynomial matrix
We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial matrix to polynomial matrix multiplication. For an input n×n matrix of degree d over ...
Arne Storjohann, Gilles Villard
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
14 years 5 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
JMLR
2006
186views more  JMLR 2006»
13 years 7 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani