Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to MKL promote ...

Dec 16, 2011 · Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to ...

Combining information from various image features has become a standard technique in concept recognition tasks. However, the optimal way of fusing the ...

Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to MKL promote ...

A recently developed non-sparse MKL variant is applied to state-of-the-art concept recognition tasks from the application domain of computer vision and ...

We review the state-of-the-art for MKL, including different formulations and algorithms for solving the related optimization problems, with the focus on their ...

Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to MKL promote ...

Diversity measure between correctly classified samples for all pairs of 32 kernels. Left: Average over all concept classes. Right: Maximum over all concept ...

Insights from Classifying Visual Concepts with Multiple Kernel Learning. Overview of attention for article published in PLOS ONE, August 2012. Altmetric Badge ...

Insights from classifying visual concepts with multiple kernel learning (English). 1 reference. stated in · Europe PubMed Central · PubMed publication ID.