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ESANN
2007
15 years 6 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
IJCAI
2007
15 years 6 months ago
Document Summarization Using Conditional Random Fields
Many methods, including supervised and unsupervised algorithms, have been developed for extractive document summarization. Most supervised methods consider the summarization task ...
Dou Shen, Jian-Tao Sun, Hua Li, Qiang Yang, Zheng ...
BMCBI
2008
177views more  BMCBI 2008»
15 years 4 months ago
Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis
Background: We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of b...
Yuanxin Xi, David M. Rocke
BMCBI
2007
127views more  BMCBI 2007»
15 years 4 months ago
The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments
Background: Isotope-coded affinity tags (ICAT) is a method for quantitative proteomics based on differential isotopic labeling, sample digestion and mass spectrometry (MS). The me...
Mario Cannataro, Giovanni Cuda, Marco Gaspari, Ser...
BMCBI
2006
207views more  BMCBI 2006»
15 years 4 months ago
A new measure for functional similarity of gene products based on Gene Ontology
Background: Gene Ontology (GO) is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods ...
Andreas Schlicker, Francisco S. Domingues, Jö...