Alpha seeding for support vector machines
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Practical Aspects of the Moreau--Yosida Regularization: Theoretical Preliminaries
SIAM Journal on Optimization
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
Multiple kernel learning, conic duality, and the SMO algorithm
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning the Kernel Function via Regularization
The Journal of Machine Learning Research
A statistical framework for genomic data fusion
Bioinformatics
Numerical Optimization: Theoretical and Practical Aspects (Universitext)
Numerical Optimization: Theoretical and Practical Aspects (Universitext)
Large Scale Multiple Kernel Learning
The Journal of Machine Learning Research
Training SVM with indefinite kernels
Proceedings of the 25th international conference on Machine learning
Localized multiple kernel learning
Proceedings of the 25th international conference on Machine learning
Proceedings of the 25th international conference on Machine learning
Multi-class Discriminant Kernel Learning via Convex Programming
The Journal of Machine Learning Research
Consistency of the Group Lasso and Multiple Kernel Learning
The Journal of Machine Learning Research
Multiple indefinite kernel learning with mixed norm regularization
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Non-monotonic feature selection
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
PRIB '09 Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics
A Convex Method for Locating Regions of Interest with Multi-instance Learning
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Feature Selection for Density Level-Sets
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
A procedure of adaptive kernel combination with kernel-target alignment for object classification
Proceedings of the ACM International Conference on Image and Video Retrieval
Building sparse multiple-kernel SVM classifiers
IEEE Transactions on Neural Networks
On multiple kernel learning with multiple labels
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Kernel Learning for Local Learning Based Clustering
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Multiple kernel active learning for image classification
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Optimising multiple kernels for SVM by genetic programming
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
Use of MKL as symbol classifier for Gujarati character recognition
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Multi-kernel SVM based classification for brain tumor segmentation of MRI multi-sequence
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A Novel Regularization Learning for Single-View Patterns: Multi-View Discriminative Regularization
Neural Processing Letters
Employing multiple-kernel support vector machines for counterfeit banknote recognition
Applied Soft Computing
Discriminative semi-supervised feature selection via manifold regularization
IEEE Transactions on Neural Networks
A multiple-kernel support vector regression approach for stock market price forecasting
Expert Systems with Applications: An International Journal
Learning what and how of contextual models for scene labeling
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Multiple kernel learning for image indexing
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Kernel feature selection to fuse multi-spectral MRI images for brain tumor segmentation
Computer Vision and Image Understanding
Medical image classification with multiple kernel learning
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Learning with uncertain kernel matrix set
Journal of Computer Science and Technology
Multiple kernel learning improved by MMD
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
A multi-scale learning framework for visual categorization
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Unsupervised selective transfer learning for object recognition
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
On feature combination and multiple kernel learning for object tracking
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Evolution strategies based adaptive Lp LS-SVM
Information Sciences: an International Journal
Relational kernel machines for learning from graph-structured RDF data
ESWC'11 Proceedings of the 8th extended semantic web conference on The semantic web: research and applications - Volume Part I
Multiple kernel active learning for facial expression analysis
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
lp-Norm Multiple Kernel Learning
The Journal of Machine Learning Research
Multiple Kernel Learning Algorithms
The Journal of Machine Learning Research
Active multiple kernel learning for interactive 3D object retrieval systems
ACM Transactions on Interactive Intelligent Systems (TiiS)
Multiple random subset-kernel learning
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Correlated multi-label feature selection
Proceedings of the 20th ACM international conference on Information and knowledge management
Discriminative compact pyramids for object and scene recognition
Pattern Recognition
Fast neighborhood component analysis
Neurocomputing
Modulating Shape Features by Color Attention for Object Recognition
International Journal of Computer Vision
Multi-kernel multi-label learning with max-margin concept network
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Separable approximate optimization of support vector machines for distributed sensing
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
Information Sciences: an International Journal
An efficient multiple-kernel learning for pattern classification
Expert Systems with Applications: An International Journal
A robust image classification scheme with sparse coding and multiple kernel learning
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
Off-line hand written input based identity determination using multi kernel feature combination
Pattern Recognition Letters
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An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes the MKL approach tractable for large-scale problems, by iteratively using existing support vector machine code. However, it turns out that this iterative algorithm needs several iterations before converging towards a reasonable solution. In this paper, we address the MKL problem through an adaptive 2-norm regularization formulation. Weights on each kernel matrix are included in the standard SVM empirical risk minimization problem with a l1 constraint to encourage sparsity. We propose an algorithm for solving this problem and provide an new insight on MKL algorithms based on block 1-norm regularization by showing that the two approaches are equivalent. Experimental results show that the resulting algorithm converges rapidly and its efficiency compares favorably to other MKL algorithms.