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ESANN
2001
15 years 8 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Patrice Wira, Jean-Philippe Urban, Julien Gresser
IJDMB
2006
86views more  IJDMB 2006»
15 years 6 months ago
Improving domain-based protein interaction prediction using biologically-significant negative dataset
: We propose a domain-based classification method to predict protein-protein interactions using probabilities of putative interacting domain pairs derived from both experimentally-...
Xiaoli Li, Soon-Heng Tan, See-Kiong Ng
CSDA
2004
129views more  CSDA 2004»
15 years 6 months ago
Gaussian process for nonstationary time series prediction
In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Exper...
Sofiane Brahim-Belhouari, Amine Bermak
CHI
2008
ACM
16 years 7 months ago
Experience sampling for building predictive user models: a comparative study
Experience sampling has been employed for decades to collect assessments of subjects' intentions, needs, and affective states. In recent years, investigators have employed au...
Ashish Kapoor, Eric Horvitz
HPCA
2004
IEEE
16 years 7 months ago
Reducing the Scheduling Critical Cycle Using Wakeup Prediction
For highest performance, a modern microprocessor must be able to determine if an instruction is ready in the same cycle in which it is to be selected for execution. This creates a...
Todd E. Ehrhart, Sanjay J. Patel