Name
Abstract | ||
|---|---|---|
Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal where we resort to the alternating optimization method: one cycle for solving SVMs in the primal by using the preconditioned conjugate gradient method and other cycle for learning the kernel weights. It is interesting to note that the kernel weights in our method can obtain analytical solutions. Most importantly, the proposed method is well suited for the manifold regularization framework in the primal since solving LapSVMs in the primal is much more effective than solving LapSVMs in the dual. In addition, we also carry out theoretical analysis for multiple kernel learning in the primal in terms of the empirical Rademacher complexity. It is found that optimizing the empirical Rademacher complexity may obtain a type of kernel weights. The experiments on some datasets are carried out to demonstrate the feasibility and effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.neunet.2013.05.003 | Neural Networks |
Keywords | Field | DocType |
primal optimization,empirical rademacher complexity,multiple kernel learning,manifold regularization,multiple kernel,optimization method,lp norm,preconditioned conjugate gradient method,lp norm mkl,training lp norm,kernel weight,data classification | Conjugate gradient method,Kernel (linear algebra),Mathematical optimization,Radial basis function kernel,Kernel embedding of distributions,Support vector machine,Multiple kernel learning,Rademacher complexity,Lp space,Artificial intelligence,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
46 | 1 | 1879-2782 |
Citations | PageRank | References |
7 | 0.44 | 28 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhizheng Liang | 1 | 162 | 17.49 |
| Shixiong Xia | 2 | 102 | 13.28 |
| Yong Zhou | 3 | 61 | 12.72 |
| Lei Zhang | 4 | 7 | 2.13 |