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NIPS
1998
15 years 7 months ago
Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations
A common way to represent a time series is to divide it into shortduration blocks, each of which is then represented by a set of basis functions. A limitation of this approach, ho...
Michael S. Lewicki, Terrence J. Sejnowski
GRID
2006
Springer
15 years 6 months ago
Snapshot Processing in Streaming Environments
Monitoring and correlation of streaming data from multiple sources is becoming increasingly important in many application areas. Example applications include automated commodities...
Daniel M. Zimmerman, K. Mani Chandy
CORR
2011
Springer
193views Education» more  CORR 2011»
14 years 10 months ago
The Synchrosqueezing algorithm: a robust analysis tool for signals with time-varying spectrum
We analyze the Synchrosqueezing transform, a consistent and invertible time-frequency analysis tool that can identify and extract oscillating components (of time-varying frequency...
Eugene Brevdo, Neven S. Fuckar, Gaurav Thakur, Hau...
MIAR
2006
IEEE
16 years 5 days ago
Pulsative Flow Segmentation in MRA Image Series by AR Modeling and EM Algorithm
Segmentation of CSF and pulsative blood flow, based on a single phase contrast MRA (PC-MRA) image can lead to imperfect classifications. In this paper, we present a novel automated...
Ali Gooya, Hongen Liao, Kiyoshi Matsumiya, Ken Mas...
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
16 years 6 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos