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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
CVPR
2009
IEEE
15 years 26 days ago
Efficient Kernels for Identifying Unbounded-Order Spatial Features
Higher order spatial features, such as doublets or triplets have been used to incorporate spatial information into the bag-of-local-features model. Due to computational limits, ...
Yimeng Zhang (Carnegie Mellon University), Tsuhan ...
ICASSP
2011
IEEE
12 years 9 months ago
Feature selection based on Multiple Kernel Learning for single-channel sound source localization using the acoustic transfer fun
This paper presents a sound source (talker) localization method using only a single microphone. In our previous work [1], we discussed the single-channel sound source localization...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
JMLR
2010
155views more  JMLR 2010»
13 years 4 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
ILP
2007
Springer
13 years 12 months ago
A Phase Transition-Based Perspective on Multiple Instance Kernels
: This paper is concerned with relational Support Vector Machines, at the intersection of Support Vector Machines (SVM) and relational learning or Inductive Logic Programming (ILP)...
Romaric Gaudel, Michèle Sebag, Antoine Corn...