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- W1971998930 abstract "We propose a scheme for rate-constrained distributed non-parametric regression using a wireless sensor network. The scheme is universal across a wide range of sensor noise models, including unbounded and nonadditive noise; it has low complexity, requiring simple operations such as uniform scalar quantization with dither and message passing between neighboring nodes in the network; and attains minimax optimality for regression functions in common smoothness classes. We present theoretical results on the trade-off between the compression rate and the MSE and demonstrate empirical performance of the scheme using simulations." @default.
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- W1971998930 date "2008-03-01" @default.
- W1971998930 modified "2023-09-27" @default.
- W1971998930 title "A low-complexity universal scheme for rate-constrained distributed regression using a wireless sensor network" @default.
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- W1971998930 doi "https://doi.org/10.1109/icassp.2008.4518098" @default.
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