QUIRE is a package for active learning by querying informative and representative examples. QUIRE selects unlabeled instances
that are both informative and representative based on the min-max view of active learning, which provides a systematic way for measuring and combining the informativeness and the representativeness. Both the single-label and multi-label versions are included.Reference:
 S.-J. Huang, R. Jin and Z.-H. Zhou. Active learning by querying informative and representative examples
. In: Advances in Neural Information Processing Systems 24 (NIPS'10), Vancouver, Canada, 2010.
 S.-J. Huang, R. Jin, and Z.-H. Zhou. Active learning by querying informative and representative examples. IEEE Transactions on Pattern Analysis and Machine Intelligence, in press.
This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Prof. Zhi-Hua Zhou
The package was developed with MATLAB 2008.ATTN2:
This package was developed by Mr. Sheng-Jun Huang (firstname.lastname@example.org). For any problem concerning the code, please feel free to contact Mr. Huang.Download: code