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» On Multiple Linear Approximations
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MMM
2009
Springer
186views Multimedia» more  MMM 2009»
15 years 6 months ago
A New Multiple Kernel Approach for Visual Concept Learning
In this paper, we present a novel multiple kernel method to learn the optimal classification function for visual concept. Although many carefully designed kernels have been propose...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...
PSIVT
2009
Springer
139views Multimedia» more  PSIVT 2009»
15 years 5 months ago
Recognizing Multiple Objects via Regression Incorporating the Co-occurrence of Categories
Abstract. Most previous methods for generic object recognition explicitly or implicitly assume that an image contains objects from a single category, although objects from multiple...
Takahiro Okabe, Yuhi Kondo, Kris M. Kitani, Yoichi...
IPPS
2000
IEEE
15 years 3 months ago
Scalable Parallel Matrix Multiplication on Distributed Memory Parallel Computers
Consider any known sequential algorithm for matrix multiplication over an arbitrary ring with time complexity ON , where 2  3. We show that such an algorithm can be parallelize...
Keqin Li
ICPR
2010
IEEE
14 years 9 months ago
Multiple Kernel Learning with High Order Kernels
Previous Multiple Kernel Learning approaches (MKL) employ different kernels by their linear combination. Though some improvements have been achieved over methods using single kerne...
Shuhui Wang, Shuqiang Jiang, Qingming Huang, Qi Ti...
ICASSP
2011
IEEE
14 years 2 months ago
Multiple kernel nonnegative matrix factorization
Kernel nonnegative matrix factorization (KNMF) is a recent kernel extension of NMF, where matrix factorization is carried out in a reproducing kernel Hilbert space (RKHS) with a f...
Shounan An, Jeong-Min Yun, Seungjin Choi