Radial Basis Function Network for Multi-task Learning

By Xuejun Liao, Lawrence Carin. 2005

35 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. Qiang Yang
2. Yu Zhang
3. Mingsheng Long
4. Amir Zamir
5. Leonidas J. Guibas
6. Dacheng Tao
7. Jitendra Malik
8. Kristen Grauman

Citations in the corpus

• A Survey on Multi-Task Learning (2017, background): “In [9], the radial basis function network, which has only one hidden layer, is extended to MTL by greedily determining the structure of the hidden layer.”
• An Information-Theoretic Approach to Transferability in Task Transfer Learning (2019, background): “The feature weight approach learns the task while regularizing feature weights with sparsity constraints, which is common in multi-task learning [29, 30].”