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» Simple and Efficient Multiple Kernel Learning by Group Lasso
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RIVF
2008
13 years 6 months ago
Simple but effective methods for combining kernels in computational biology
Complex biological data generated from various experiments are stored in diverse data types in multiple datasets. By appropriately representing each biological dataset as a kernel ...
Hiroaki Tanabe, Tu Bao Ho, Canh Hao Nguyen, Saori ...
DAGM
2010
Springer
13 years 6 months ago
Random Fourier Approximations for Skewed Multiplicative Histogram Kernels
Abstract. Approximations based on random Fourier features have recently emerged as an efficient and elegant methodology for designing large-scale kernel machines [4]. By expressing...
Fuxin Li, Catalin Ionescu, Cristian Sminchisescu
ICML
2010
IEEE
13 years 6 months ago
A scalable trust-region algorithm with application to mixed-norm regression
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
BMCBI
2008
228views more  BMCBI 2008»
13 years 5 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
WEBI
2010
Springer
13 years 3 months ago
Image Set Classification Using Multi-layer Multiple Instance Learning with Application to Cannabis Website Classification
We propose using multi-layer multiple instance learning (MMIL) for image set classification and applying it to the task of cannabis website classification. We treat each image as a...
Nianhua Xie, Haibin Ling, Weiming Hu