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» A Data Model for Effectively Computable Functions
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ICONIP
1998
14 years 11 months ago
Computing Iterative Roots with Neural Networks
Many real processes are composed of a n-fold repetition of some simpler process. If the whole process can be modelled with a neural network, we present a method to derive a model ...
Lars Kindermann
CIKM
2008
Springer
14 years 11 months ago
Trada: tree based ranking function adaptation
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...
BIBM
2010
IEEE
151views Bioinformatics» more  BIBM 2010»
14 years 7 months ago
Probabilistic topic modeling for genomic data interpretation
Recently, the concept of a species containing both core and distributed genes, known as the supra- or pangenome theory, has been introduced. In this paper, we aim to develop a new ...
Xin Chen, Xiaohua Hu, Xiajiong Shen, Gail Rosen
ICCS
2003
Springer
15 years 3 months ago
A Method of Hidden Markov Model Optimization for Use with Geophysical Data Sets
Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements...
Robert A. Granat
NIPS
2003
14 years 11 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