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» Estimating Missing Data in Data Streams
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SSDBM
2006
IEEE
167views Database» more  SSDBM 2006»
14 years 3 months ago
Exploring Data Streams with Nonparametric Estimators
A variety of real-world applications requires a meaningful online analysis of transient data streams. An important building block of many analysis tasks is the characterization of...
Christoph Heinz, Bernhard Seeger
ESCAPE
2007
Springer
266views Algorithms» more  ESCAPE 2007»
14 years 4 months ago
CR-precis: A Deterministic Summary Structure for Update Data Streams
We present deterministic sub-linear space algorithms for a number of problems over update data streams, including, estimating frequencies of items and ranges, finding approximate ...
Sumit Ganguly, Anirban Majumder
NIPS
2003
13 years 11 months ago
Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data
Discrete Fourier transforms and other related Fourier methods have been practically implementable due to the fast Fourier transform (FFT). However there are many situations where ...
Amos J. Storkey
NECO
1998
121views more  NECO 1998»
13 years 9 months ago
Nonlinear Time-Series Prediction with Missing and Noisy Data
We derive solutions for the problem of missing and noisy data in nonlinear timeseries prediction from a probabilistic point of view. We discuss different approximations to the so...
Volker Tresp, Reimar Hofmann
ICASSP
2008
IEEE
14 years 4 months ago
Robust speaker identification using combined feature selection and missing data recognition
Missing data techniques have been recently applied to speaker recognition to increase performance in noisy environments. The drawback of these techniques is the vulnerability of t...
Daniel Pullella, Marco Kühne, Roberto Togneri