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» Sublinear Optimization for Machine Learning
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FTML
2008
185views more  FTML 2008»
13 years 7 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan
IJON
2006
146views more  IJON 2006»
13 years 7 months ago
Feature selection and classification using flexible neural tree
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Yuehui Chen, Ajith Abraham, Bo Yang
NPL
2006
130views more  NPL 2006»
13 years 7 months ago
A Fast Feature-based Dimension Reduction Algorithm for Kernel Classifiers
This paper presents a novel dimension reduction algorithm for kernel based classification. In the feature space, the proposed algorithm maximizes the ratio of the squared between-c...
Senjian An, Wanquan Liu, Svetha Venkatesh, Ronny T...
IJBRA
2007
80views more  IJBRA 2007»
13 years 7 months ago
On predicting secondary structure transition
A function of a protein is dependent on its structure; therefore, predicting a protein structure from an amino acid sequence is an active area of research. Optimally predicting a ...
Raja Loganantharaj, Vivek Philip
TEC
2008
139views more  TEC 2008»
13 years 7 months ago
Genetic Programming Approaches for Solving Elliptic Partial Differential Equations
In this paper, we propose a technique based on genetic programming (GP) for meshfree solution of elliptic partial differential equations. We employ the least-squares collocation pr...
Andras Sobester, Prasanth B. Nair, Andy J. Keane