@inproceedings{4683e97fd326446c8d997b5f8f432b94,

title = "Universal linear least-squares prediction in the presence of noise",

abstract = "Universal linear least squares prediction of real-valued bounded individual sequences in the presence of additive bounded noise is considered. It is shown that there is a sequential predictor observing noisy samples of the sequence to be predicted only, whose loss in terms of the noise-free sequence is asymptotically as small as that of the best batch predictor out of the class of all linear predictors with knowledge of the entire noisy sequence in advance.",

keywords = "Least squares, Linear, Noise, Prediction",

author = "Zeitler, {Georg C.} and Singer, {Andrew C.}",

year = "2007",

doi = "10.1109/SSP.2007.4301331",

language = "English (US)",

isbn = "142441198X",

series = "IEEE Workshop on Statistical Signal Processing Proceedings",

pages = "611--614",

booktitle = "2007 IEEE/SP 14th Workshop on Statistical Signal Processing, SSP 2007, Proceedings",

note = "2007 IEEE/SP 14th WorkShoP on Statistical Signal Processing, SSP 2007 ; Conference date: 26-08-2007 Through 29-08-2007",

}