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» Input Modeling Using Quantile Statistical Methods
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NIPS
2003
15 years 2 months ago
Nonstationary Covariance Functions for Gaussian Process Regression
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...
Christopher J. Paciorek, Mark J. Schervish
BMCBI
2004
108views more  BMCBI 2004»
15 years 19 days ago
Enhanced protein domain discovery using taxonomy
Background: It is well known that different species have different protein domain repertoires, and indeed that some protein domains are kingdom specific. This information has not ...
Lachlan James M. Coin, Alex Bateman, Richard Durbi...
109
Voted
ICPR
2010
IEEE
14 years 10 months ago
Online Next-Best-View Planning for Accuracy Optimization Using an Extended E-Criterion
Next-best-view (NBV) planning is an important aspect for three-dimensional (3D) reconstruction within controlled environments, such as a camera mounted on a robotic arm. NBV metho...
Michael Trummer, Christoph Munkelt, Joachim Denzle...
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 4 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
104
Voted
JCST
2008
138views more  JCST 2008»
15 years 22 days ago
Predicting Chinese Abbreviations from Definitions: An Empirical Learning Approach Using Support Vector Regression
In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however, make keyword-based approaches less effective. This paper presents an em...
Xu Sun, Houfeng Wang, Bo Wang 0003