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» Learning Nonlinear Manifolds from Time Series
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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
15 years 10 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
78
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AIPR
2005
IEEE
15 years 3 months ago
Hyperspectral Detection Algorithms: Operational, Next Generation, on the Horizon
Abstract—The multi-band target detection algorithms implemented in hyperspectral imaging systems represent perhaps the most successful example of image fusion. A core suite of su...
A. Schaum
CAEPIA
2003
Springer
15 years 2 months ago
Enhancing Consistency Based Diagnosis with Machine Learning Techniques
This paper proposes a diagnosis architecture that integrates consistency based diagnosis with induced time series classifiers, trying to combine the advantages of both methods. Co...
Carlos J. Alonso, Juan José Rodrígue...
ICCS
2007
Springer
15 years 3 months ago
Dynamic Tracking of Facial Expressions Using Adaptive, Overlapping Subspaces
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Dimitris N. Metaxas, Atul Kanaujia, Zhiguo Li
KDD
2004
ACM
198views Data Mining» more  KDD 2004»
15 years 3 months ago
Mining traffic data from probe-car system for travel time prediction
We are developing a technique to predict travel time of a vehicle for an objective road section, based on real time traffic data collected through a probe-car system. In the area ...
Takayuki Nakata, Jun-ichi Takeuchi