Probabilistic Multi-Label Classification with Sparse Feature Learning

By Yuhong Guo, Wei Xue. 2013

42 citations recorded by the source corpus.

How researchers see this paper

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

1. Dacheng Tao
2. Jie Gui
3. Jieping Ye
4. Yu Zhang
5. Zhenan Sun
6. Tien-Ping Tan
7. Shuiwang Ji
8. Xiaoqian Jiang

Citations in the corpus

• Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis (2019, methodology): “As a result, the l2,1-norm is commonly used in multi-task feature learning to perform feature selection as it can induce structural sparsity [13, 21, 24, 32].”
• Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis (2015, methodology): “In this paper, we proposed to use multi-task learning strategy [4], [8], [9] to overcome the above difficulty.”
• Feature Selection Based on Structured Sparsity: A Comprehensive Study (2017, background): “In [116], a probabilistic multilabel learning model based on novel sparse feature learning is proposed.”