95 citations · 102 across the 15 of their papers we have counts for
5 papers · 1 filter
One-shot Machine Teaching: Cost Very Few Examples to Converge Faster
Chen Zhang, Xiaofeng Cao, Yi Chang +1
Artificial intelligence is to teach machines to take actions like humans. To achieve intelligent teaching, the machine learning community becomes to think about a promising topic n…
Data-Efficient Learning via Minimizing Hyperspherical Energy
Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang
Deep learning on large-scale data is dominant nowadays. The unprecedented scale of data has been arguably one of the most important driving forces for the success of deep learning.…
A Survey of Learning on Small Data: Generalization, Optimization, and Challenge
Xiaofeng Cao, Weixin Bu, Shengjun Huang +4
Learning on big data brings success for artificial intelligence (AI), but the annotation and training costs are expensive. In future, learning on small data that approximates the g…
Black-box Generalization of Machine Teaching
Xiaofeng Cao, Yaming Guo, Ivor W. Tsang +1
Hypothesis-pruning maximizes the hypothesis updates for active learning to find those desired unlabeled data. An inherent assumption is that this learning manner can derive those u…
Hyperbolic Uncertainty Aware Semantic Segmentation
Bike Chen, Wei Peng, Xiaofeng Cao +1
Semantic segmentation (SS) aims to classify each pixel into one of the pre-defined classes. This task plays an important role in self-driving cars and autonomous drones. In SS, man…