26 citations · 65 across the 6 of their papers we have counts for
4 papers · 1 filter
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion
Xian-Jin Gui, Wei Wang, Zhang-Hao Tian
Deep neural networks need large amounts of labeled data to achieve good performance. In real-world applications, labels are usually collected from non-experts such as crowdsourcing…
Deep Multi-Task Learning via Generalized Tensor Trace Norm
Yi Zhang, Yu Zhang, Wei Wang
The trace norm is widely used in multi-task learning as it can discover low-rank structures among tasks in terms of model parameters. Nowadays, with the emerging of big datasets an…
Theoretical Foundation of Co-Training and Disagreement-Based Algorithms
Wei Wang, Zhi-Hua Zhou
Disagreement-based approaches generate multiple classifiers and exploit the disagreement among them with unlabeled data to improve learning performance. Co-training is a representa…
Multi-View Active Learning in the Non-Realizable Case
Wei Wang, Zhi-Hua Zhou
The sample complexity of active learning under the realizability assumption has been well-studied. The realizability assumption, however, rarely holds in practice. In this paper, w…