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» Dynamically Adapting Kernels in Support Vector Machines
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146
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HPDC
2005
IEEE
15 years 9 months ago
Increasing application performance in virtual environments through run-time inference and adaptation
Virtual machine distributed computing greatly simplifies the use of widespread computing resources by lowering the abstraction, benefiting both resource providers and users. Tow...
Ananth I. Sundararaj, Ashish Gupta, Peter A. Dinda
166
Voted
ML
2010
ACM
142views Machine Learning» more  ML 2010»
15 years 2 months ago
Fast adaptive algorithms for abrupt change detection
We propose two fast algorithms for abrupt change detection in streaming data that can operate on arbitrary unknown data distributions before and after the change. The first algor...
Daniel Nikovski, Ankur Jain
129
Voted
ICSR
2004
Springer
15 years 9 months ago
A Metamodel-Based Approach for the Dynamic Reconfiguration of Component-Based Software
Non-stop and highly available applications need to be dynamically adapted to new conditions in their execution environment, to new user requirements or to some situations usually u...
Abdelmadjid Ketfi, Noureddine Belkhatir
142
Voted
COMPGEOM
2009
ACM
15 years 10 months ago
Coresets for polytope distance
Following recent work of Clarkson, we translate the coreset framework to the problems of finding the point closest to the origin inside a polytope, finding the shortest distance...
Bernd Gärtner, Martin Jaggi
148
Voted
ICCV
2003
IEEE
16 years 5 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...