Online Kernel Selection: Algorithms and Evaluations
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being used, identifying good kernels among a set of given kernels is important to the success of kernel methods. A straightfor...
Saved in:
Main Authors: | YANG, Tianbao, MAHDAVI, Mehrdad, JIN, Rong, YI, Jinfeng, HOI, Steven C. H. |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2012
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/2344 https://ink.library.smu.edu.sg/context/sis_research/article/3344/viewcontent/Online_Kernel_Selection_Algorithms_and_Evaluations.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Online Multiple Kernel Learning: Algorithms and Mistake Bounds
by: JIN, Rong, et al.
Published: (2010) -
Online sparse passive aggressive learning with kernels
by: LU, Jing, et al.
Published: (2016) -
Fast bounded online gradient descent algorithms for scalable kernel-based online learning
by: ZHAO, Peilin, et al.
Published: (2012) -
Online Multiple Kernel Classification
by: HOI, Steven C. H., et al.
Published: (2013) -
Online AUC maximization
by: ZHAO, Peilin, et al.
Published: (2011)