Wang, Dongdong, Li, Yandong, Wang, Liqiang, and Gong, Boqing. Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation From a Blackbox Model. Retrieved from https://par.nsf.gov/biblio/10203569. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Web. doi:10.1109/cvpr42600.2020.00157.

Wang, Dongdong, Li, Yandong, Wang, Liqiang, & Gong, Boqing. Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation From a Blackbox Model. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), (). Retrieved from https://par.nsf.gov/biblio/10203569. https://doi.org/10.1109/cvpr42600.2020.00157

Wang, Dongdong, Li, Yandong, Wang, Liqiang, and Gong, Boqing. "Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation From a Blackbox Model". IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (). Country unknown/Code not available. https://doi.org/10.1109/cvpr42600.2020.00157. https://par.nsf.gov/biblio/10203569.

@article{osti_10203569,
place = {Country unknown/Code not available}, title = {Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation From a Blackbox Model}, url = {https://par.nsf.gov/biblio/10203569}, DOI = {10.1109/cvpr42600.2020.00157}, abstractNote = {}, journal = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, author = {Wang, Dongdong and Li, Yandong and Wang, Liqiang and Gong, Boqing}, editor = {null} }