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» Gaussian process for nonstationary time series prediction
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AAAI
2012
11 years 11 months ago
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images
Pre-symptomatic drought stress prediction is of great relevance in precision plant protection, ultimately helping to meet the challenge of “How to feed a hungry world?”. Unfor...
Kristian Kersting, Zhao Xu, Mirwaes Wahabzada, Chr...
SDM
2009
SIAM
172views Data Mining» more  SDM 2009»
14 years 5 months ago
Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach.
This paper is concerned with the task of travel-time prediction for an arbitrary origin-destination pair on a map. Unlike most of the existing studies, which focus only on a parti...
Sei Kato, Tsuyoshi Idé
CORR
2011
Springer
213views Education» more  CORR 2011»
13 years 3 months ago
Adapting to Non-stationarity with Growing Expert Ensembles
Forecasting sequences by expert ensembles generally assumes stationary or near-stationary processes; however, in complex systems and many real-world applications, we are frequentl...
Cosma Rohilla Shalizi, Abigail Z. Jacobs, Aaron Cl...
TSMC
2008
102views more  TSMC 2008»
13 years 8 months ago
Generalized Cost-Function-Based Forecasting for Periodically Measured Nonstationary Traffic
Abstract-- In this paper, we address the issue of forecasting for periodically measured nonstationary traffic based on statistical time series modeling. Often with time series base...
Balaji Krithikaivasan, Yong Zeng, Deep Medhi
MIAR
2006
IEEE
14 years 2 months 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...