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TIP
2010
141views more  TIP 2010»
13 years 2 months ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina
ICASSP
2011
IEEE
12 years 11 months ago
Generic object recognition using automatic region extraction and dimensional feature integration utilizing multiple kernel learn
Recently, in generic object recognition research, a classification technique based on integration of image features is garnering much attention. However, with a classifying techn...
Toru Nakashika, Akira Suga, Tetsuya Takiguchi, Yas...
PDCAT
2004
Springer
14 years 28 days ago
Locabus: A Kernel to Kernel Communication Channel for Cluster Computing
Abstract. This paper proposes a kernel to kernel communication system for use in cluster computers. It is implemented directly on the Ethernet data link layer. This allows use of E...
Paul Werstein, Mark Pethick, Zhiyi Huang
ALT
2003
Springer
14 years 4 months ago
Kernel Trick Embedded Gaussian Mixture Model
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
Jingdong Wang, Jianguo Lee, Changshui Zhang
JMLR
2010
155views more  JMLR 2010»
13 years 6 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...