230 search results - page 16 / 46 » Smooth Optimization for Effective Multiple Kernel Learning |
102
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ML
2002
ACM
14 years 9 months ago
2002
ACM
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
89
Voted
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
In this paper, we present a novel semisupervised regression algorithm working on multiclass data that may lie on multiple manifolds. Unlike conventional manifold regression algori...
CIDM
2007
IEEE
15 years 1 months ago
2007
IEEE
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
94
Voted
ICDM
2006
IEEE
15 years 3 months ago
2006
IEEE
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...