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NIPS
1998
13 years 9 months ago
Dynamically Adapting Kernels in Support Vector Machines
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
Nello Cristianini, Colin Campbell, John Shawe-Tayl...
IJON
2007
99views more  IJON 2007»
13 years 7 months ago
Criticality of avalanche dynamics in adaptive recurrent networks
In many studies of self-organized criticality (SOC), branching processes were used to model the dynamics of the activity of the system during avalanches. This mathematical simpliï...
Anna Levina, Udo Ernst, J. Michael Herrmann
ICML
2000
IEEE
14 years 8 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore
3DPVT
2006
IEEE
183views Visualization» more  3DPVT 2006»
14 years 2 months ago
High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming
We present a stereo algorithm that achieves high quality results while maintaining real-time performance. The key idea is simple: we introduce an adaptive aggregation step in a dy...
Liang Wang, Miao Liao, Minglun Gong, Ruigang Yang,...
ICDCS
2005
IEEE
14 years 1 months ago
Fine-Grain Adaptive Compression in Dynamically Variable Networks
Despite voluminous previous research on adaptive compression, we found significant challenges when attempting to fully utilize both network bandwidth and CPU. We describe the Fine...
Calton Pu, Lenin Singaravelu