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Many problems in machine learning and computer vision consist of predicting multi-dimensional output vectors given a specific set of input features. In many of these problems, there exist inherent temporal and spacial dependencies between the output vectors, as well as repeating output patterns and input-output associations, that can provide more robust and accurate predictors when modelled properly...
In this paper, a support vector regression (SVR) based method is proposed to detect a geometric feature such as line equation, corner point and angle degree between straight lines in an image. Digital image with geometric figures is collected and transmitted into computer. Median filter is used to reduce noise in the original gray scale image. Then image contour with single-pixel width is obtained...
In this paper a novel linear regression model is proposed to mine related queries from query logs. Three types of association relationships between queries are identified and leveraged in our model, which include query session co-occurence, URL-clicked sharing and text similarity. Previous work directly applies part of these relations, which may be largely affected by the noise in query logs, such...
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