Distributed Kernel Regression: An Algorithm for Training Collaboratively

@article{Predd2006DistributedKR,
  title={Distributed Kernel Regression: An Algorithm for Training Collaboratively},
  author={Joel B. Predd and Sanjeev R. Kulkarni and H. Vincent Poor},
  journal={2006 IEEE Information Theory Workshop - ITW '06 Punta del Este},
  year={2006},
  pages={332-336}
}
This paper addresses the problem of distributed learning under communication constraints, motivated by distributed signal processing in wireless sensor networks and data mining with distributed databases. After formalizing a general model for distributed learning, an algorithm for collaboratively training regularized kernel least-squares regression estimators is derived. Noting that the algorithm can be viewed as an application of successive orthogonal projection algorithms, its convergence… CONTINUE READING
Highly Cited
This paper has 40 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 27 extracted citations

Real-Time Semiparametric Regression for Distributed Data Sets

IEEE Transactions on Knowledge and Data Engineering • 2015
View 1 Excerpt

In-network online asynchronous regression over a wireless network

2014 Twentieth National Conference on Communications (NCC) • 2014
View 3 Excerpts

Strategies for principal component analysis in wireless sensor networks

2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM) • 2014
View 1 Excerpt

Distributed least square support vector regression for environmental field estimation

2011 IEEE International Conference on Information and Automation • 2011
View 1 Excerpt

References

Publications referenced by this paper.
Showing 1-10 of 18 references

Similar Papers

Loading similar papers…