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IJBRA
2006
107views more  IJBRA 2006»
14 years 10 months ago
Probabilistic models for biological sequences: selection and Maximum Likelihood estimation
: Probabilistic models for biological sequences (DNA and proteins) are frequently used in bioinformatics. We describe statistical tests designed to detect the order of dependency a...
Svetlana Ekisheva, Mark Borodovsky
BIBE
2006
IEEE
135views Bioinformatics» more  BIBE 2006»
15 years 4 months ago
Evidence of Multiple Maximum Likelihood Points for a Phylogenetic Tree
An interesting and important, but largely ignored question associated with the ML method is whether there exists only a single maximum likelihood point for a given phylogenetic tr...
Bing Bing Zhou, Monther Tarawneh, Pinghao Wang, Da...
FSKD
2006
Springer
190views Fuzzy Logic» more  FSKD 2006»
15 years 1 months ago
A Maximum Entropy Model Based Answer Extraction for Chinese Question Answering
We regard answer extraction of Question Answering (QA) system as a classification problem, classifying answer candidate sentences into positive or negative. To confirm the feasibil...
Ang Sun, Minghu Jiang, Yanjun Ma
ML
2006
ACM
122views Machine Learning» more  ML 2006»
14 years 9 months ago
PRL: A probabilistic relational language
In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
Lise Getoor, John Grant
ML
2006
ACM
110views Machine Learning» more  ML 2006»
14 years 9 months ago
Classification-based objective functions
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Michael Rimer, Tony Martinez