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» Feature space perspectives for learning the kernel
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NAACL
2007
13 years 9 months ago
Kernel Regression Based Machine Translation
We present a novel machine translation framework based on kernel regression techniques. In our model, the translation task is viewed as a string-to-string mapping, for which a reg...
Zhuoran Wang, John Shawe-Taylor, Sándor Sze...
TSP
2008
89views more  TSP 2008»
13 years 7 months ago
The Kernel Least-Mean-Square Algorithm
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
Weifeng Liu, Puskal P. Pokharel, Jose C. Principe
ICML
2009
IEEE
14 years 8 months ago
Partial order embedding with multiple kernels
We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pairwise distances. Partial order cons...
Brian McFee, Gert R. G. Lanckriet
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 8 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
CVPR
2011
IEEE
13 years 4 months ago
Sharing Features Between Objects and Their Attributes
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
Sung Ju Hwang, Fei Sha, Kristen Grauman