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ML
2007
ACM
144views Machine Learning» more  ML 2007»
15 years 4 months ago
Invariant kernel functions for pattern analysis and machine learning
In many learning problems prior knowledge about pattern variations can be formalized and beneficially incorporated into the analysis system. The corresponding notion of invarianc...
Bernard Haasdonk, Hans Burkhardt
BIBM
2008
IEEE
106views Bioinformatics» more  BIBM 2008»
15 years 7 months ago
Invariance Kernel of Biological Regulatory Networks
: The analysis of Biological Regulatory Network (BRN) leads to compute the set of the possible behaviours of the biological components. These behaviours are seen as trajectories an...
Jamil Ahmad, Olivier Roux
GFKL
2007
Springer
164views Data Mining» more  GFKL 2007»
15 years 9 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
NECO
2010
97views more  NECO 2010»
15 years 3 months ago
Rademacher Chaos Complexities for Learning the Kernel Problem
In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
Yiming Ying, Colin Campbell
CORR
2010
Springer
178views Education» more  CORR 2010»
15 years 5 months ago
Fast Histograms using Adaptive CUDA Streams
Histograms are widely used in medical imaging, network intrusion detection, packet analysis and other streambased high throughput applications. However, while porting such software...
Sisir Koppaka, Dheevatsa Mudigere, Srihari Narasim...