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Multiple kernel learning

Known as: MKL 
Multiple kernel learning refers to a set of machine learning methods that use a predefined set of kernels and learn an optimal linear or non-linear… 
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Related topics

Related topics

11 relations

Broader (1)

Data mining
Elastic net regularizationGibbs samplingKernel methodMATLAB

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2013
2013
Multi-task Multiple Kernel Learning
We present a general regularization-based framework for Multi-task learning (MTL), in which the similarity between tasks can be… 
Highly Cited
2012
Highly Cited
2012
Fourier Kernel Learning
Approximations based on random Fourier embeddings have recently emerged as an efficient and formally consistent methodology to… 
2012
2012
Evaluation and improvement of spectral features for the detection of buried explosive hazards using forward-looking ground-penetrating radar
We provide an evaluation of spectral features extracted from the signal return of a forward-looking ground penetrating radar to… 
2011
2011
Learning neighborhood cooccurrence statistics of sparse features for human activity recognition
A common approach to activity recognition has been the use of histogram of codewords computed from Spatio Temporal Interest… 
2011
2011
Wavelet kernel learning
2010
2010
Multiple Kernel Learning with High Order Kernels
Previous Multiple Kernel Learning approaches (MKL) employ different kernels by their linear combination. Though some improvements… 
2009
2009
Bayesian Localized Multiple Kernel Learning
Multiple kernel learning approaches to multi-view learning [1, 11, 7] have recently become very popular since they can easily… 
2009
2009
Multiple Kernel Learning for Object Classification
: Combining information from various image descriptors has become a standard technique for image classification tasks. Multiple… 
Highly Cited
2009
Highly Cited
2009
On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation
Motivated from real world problems, like object categorization, we study a particular mixed-norm regularization for Multiple… 
2008
2008
Multiple kernel learning for speaker verification
Many speaker verification (SV) systems combine multiple classifiers using score-fusion to improve system performance. For SVM… 
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