Distributed estimation and learning over heterogeneous networks
We consider several estimation and learning problems that networked agents face when making decisions given their uncertainty about an unknown variable. Our methods are designed to efficiently deal with heterogeneity in both size and quality of the observed data, as well as heterogeneity over time (...
Main Authors: | Rahimian, Mohammad Amin, Jadbabaie-Moghadam, Ali |
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Other Authors: | Massachusetts Institute of Technology. Institute for Data, Systems, and Society |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2017
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Online Access: | http://hdl.handle.net/1721.1/110364 |
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