This paper presents a method of online sketchy shape recognition that can adapt to different user sketching styles. The adaptation principle is based on incremental active learning...
Zhengxing Sun, Liu Wenyin, Binbin Peng, Bin Zhang,...
Object detection with a learned classifier has been applied successfully to difficult tasks such as detecting faces and pedestrians. Systems using this approach usually learn the ...
We describe a general framework for online multiclass learning based on the notion of hypothesis sharing. In our framework sets of classes are associated with hypotheses. Thus, al...
Michael Fink 0002, Shai Shalev-Shwartz, Yoram Sing...
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...