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» Learning to Select a Ranking Function
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ICPR
2008
IEEE
14 years 2 months ago
Ranking the local invariant features for the robust visual saliencies
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Shengping Xia, Peng Ren, Edwin R. Hancock
AAAI
1994
13 years 9 months ago
Learning to Select Useful Landmarks
To navigate effectively, an autonomous agent must be able to quickly and accurately determine its current location. Given an initial estimate of its position (perhaps based on dea...
Russell Greiner, Ramana Isukapalli
KDD
2006
ACM
191views Data Mining» more  KDD 2006»
14 years 8 months ago
Beyond classification and ranking: constrained optimization of the ROI
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...
Lian Yan, Patrick Baldasare
CIKM
2006
Springer
13 years 11 months ago
A comparative study on classifying the functions of web page blocks
In this paper, we study the problem of learning block classification models to estimate block functions. We distinguish general models, which are learned across multiple sites, an...
Xiangye Xiao, Qiong Luo, Xing Xie, Wei-Ying Ma
ICML
2009
IEEE
14 years 2 months ago
Non-monotonic feature selection
We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinator...
Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, ...