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» Constraint Programming for Data Mining and Machine Learning
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GFKL
2007
Springer
164views Data Mining» more  GFKL 2007»
15 years 7 months ago
Classification with Invariant Distance Substitution Kernels
Kernel methods offer a flexible toolbox for pattern analysis and machine learning. A general class of kernel functions which incorporates known pattern invariances are invariant d...
Bernard Haasdonk, Hans Burkhardt
ICCV
2003
IEEE
16 years 5 months ago
Landmark-based Shape Deformation with Topology-Preserving Constraints
This paper presents a novel approach for landmarkbased shape deformation, in which fitting error and shape difference are formulated into a support vector machine (SVM) regression...
Song Wang, Jim Xiuquan Ji, Zhi-Pei Liang
ICML
2009
IEEE
16 years 3 months ago
A convex formulation for learning shared structures from multiple tasks
Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously. In this paper, we consider the problem of learning shared s...
Jianhui Chen, Lei Tang, Jun Liu, Jieping Ye
CORR
2012
Springer
185views Education» more  CORR 2012»
13 years 10 months ago
Bayesian network learning with cutting planes
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...
James Cussens
ALIFE
1999
15 years 2 months ago
An Approach to Biological Computation: Unicellular Core-Memory Creatures Evolved Using Genetic Algorithms
A novel machine language genetic programming system that uses one-dimensional core memories is proposed and simulated. The core is compared to a biochemical reaction space, and in ...
Hikeaki Suzuki