Title :
Consistency in a model for distributed learning with specialists
Author :
Predd, Joel B. ; Kulkarni, Sanjeev R. ; Poor, H. Vincent
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
fDate :
27 June-2 July 2004
Abstract :
Motivated by sensor networks and traditional methods of statistical pattern recognition, a model for distributed learning is formulated. The model is in line with learning models considered in the context of Stone-type classifiers, but differs in the dependency structure of the sampling process; questions of universal consistency are addressed.
Keywords :
array signal processing; distributed sensors; pattern classification; signal sampling; distributed learning model; sampling process; sensor network; statistical pattern recognition; stone-type classifier; Context modeling; Distributed databases; Intelligent networks; Monitoring; Pattern recognition; Random variables; Sampling methods; Sensor arrays; Statistical distributions; Training data;
Conference_Titel :
Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
Print_ISBN :
0-7803-8280-3
DOI :
10.1109/ISIT.2004.1365502
