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CSDA
2010
100views more  CSDA 2010»
13 years 6 months ago
Least squares estimation of nonlinear spatial trends
The goal of this work is to study the asymptotic and finite sample properties of an estimator of a nonlinear regression function when errors are spatially correlated, and when the...
Rosa M. Crujeiras, Ingrid Van Keilegom
DATE
2006
IEEE
93views Hardware» more  DATE 2006»
14 years 1 months ago
Restructuring field layouts for embedded memory systems
In many computer systems with large data computations, the delay of memory access is one of the major performance bottlenecks. In this paper, we propose an enhanced field remappi...
Keoncheol Shin, Jungeun Kim, Seonggun Kim, Hwansoo...
UAI
2000
13 years 9 months ago
The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data
This paper is about the use of metric data structures in high-dimensionalor non-Euclidean space to permit cached sufficientstatisticsaccelerationsof learning algorithms. It has re...
Andrew W. Moore
UAI
2008
13 years 9 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
14 years 17 days ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...