Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data

By Kai Ni, John William Paisley, Lawrence Carin, David B. Dunson. 2008

17 citations recorded by the source corpus.

Subfields: Artificial Intelligence

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. Qiang Yang
2. Yu Zhang
3. David B. Dunson
4. Abel Rodríguez
5. Alan E. Gelfand
6. Mingsheng Long
7. Jianmin Wang
8. Michael I. Jordan

Citations in the corpus

• A Survey on Multi-Task Learning (2017, methodology): “Moreover, a nested Dirichlet process is proposed in [62], [63] to use Dirichlet processes to learn both task clusters and the state structure of an infinite hidden Markov model, which handles sequential data in each task.”
• The Nested Dirichlet Process (2008, methodology): “Ni, K., Paisley, J., Carin, L., and Dunson, D. B. (2008), “Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data,” IEEE Transactions on Signal Processing, 56, 3918–3931.”