Multi-task compressive sensing with Dirichlet process priors

By Yuting Qi, Dehong Liu, David B. Dunson, Lawrence Carin. 2008

62 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Mechanics, Signal Processing

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. Shuicheng Yan
3. Thomas S. Huang
4. Julien Mairal
5. Yu Zhang
6. Guillermo Sapiro
7. Dacheng Tao
8. Yi Ma

In Computational Mechanics

1. Lei Zhang
2. Julien Mairal
3. Shuicheng Yan
4. Thomas S. Huang
5. Guillermo Sapiro
6. Yi Ma
7. Francis R. Bach
8. Qiang Yang

In Signal Processing

1. Julien Mairal
2. Thomas S. Huang
3. Yi Ma
4. Shuicheng Yan
5. Guillermo Sapiro
6. John Wright
7. Dimitris Samaras
8. Qiang Yang

Citations in the corpus

• A Survey on Multi-Task Learning (2017, methodology): “This model is extended in [59], [60] to a case where different tasks in a task cluster share useful features via a matrix stick-breaking process and a betaBernoulli hierarchical prior, respectively, and in [61] where each task is a compressive sensing task.”
• Multi-Task Learning of Gaussian Graphical Models (2010, background): “, 2009), classification (Jebara, 2004), compressive sensing (Qi et al., 2008), reinforcement learning (Wilson et al.”
• Sparse Representation for Computer Vision and Pattern Recognition (2010, background): “, [22] and references therein, is yet another interesting area for future research.”
• Multi-Task Learning for Subspace Segmentation (2015, methodology): “Close inspection reveals a strong relationship with the updates from (Qi et al., 2008), the primary difference being how the parameter W is iterated.”