Smart Multitask Bregman Clustering and Multitask Kernel Clustering

By Xianchao Zhang, Xiaotong Zhang, 刘晗. 2015

25 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Media Technology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. 刘晗
2. Xiaotong Zhang
3. Xianchao Zhang
4. Jiebo Luo
5. Yu Zhang
6. Qiang Yang
7. Min-Ling Zhang
8. Zhi-Hua Zhou

In Media Technology

1. Xianchao Zhang
2. Xiaotong Zhang
3. 刘晗
4. Jiebo Luo

Citations in the corpus

• A Survey on Multi-View Clustering (2017, unknown): “Multi-task clustering aims to improve the performance of unsupervised clustering tasks, such as [123], [124], [125], [126], [127].”
• Multi-Task Clustering with Model Relation Learning (2018, methodology): “…learning multi-task clustering (LSSMTC) method [Gu and Zhou, 2009], the smart multi-task Bregman and Kernel clustering (S-MBC and S-MKC) methods [Zhang et al. , 2015], the convex discriminative multi-task feature clustering (DMTFC) method [Zhang, 2015], the convex discriminative multi-task…”
• Self-Adapted Multi-Task Clustering (2016, methodology): “We also compare SAMTC with the multi-task clustering methods which work for completely related tasks: the shared subspace learning multi-task clustering (LSSMTC) method [Gu and Zhou, 2009] and the convex discriminative multi-task feature clustering (MTFC) method [Zhang, 2015].”