Timezone: »

Weakly Supervised Regression with Interval Targets
Xin Cheng · Yuzhou Cao · Ximing Li · Bo An · Lei Feng

Tue Jul 25 05:00 PM -- 06:30 PM (PDT) @ Exhibit Hall 1 #517

This paper investigates an interesting weakly supervised regression setting called regression with interval targets (RIT). Although some of the previous methods on relevant regression settings can be adapted to RIT, they are not statistically consistent, and thus their empirical performance is not guaranteed. In this paper, we provide a thorough study on RIT. First, we proposed a novel statistical model to describe the data generation process for RIT and demonstrate its validity. Second, we analyze a simple selecting method for RIT, which selects a particular value in the interval as the target value to train the model. Third, we propose a statistically consistent limiting method for RIT to train the model by limiting the predictions to the interval. We further derive an estimation error bound for our limiting method. Finally, extensive experiments on various datasets demonstrate the effectiveness of our proposed method.

Author Information

Xin Cheng (Chongqing University)
Yuzhou Cao (China Agricultural University)
Ximing Li (Jilin University)
Bo An (Nanyang Technological University)
Lei Feng (Nanyang Technological University, Singapore)

More from the Same Authors