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SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 2 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
BMCBI
2008
165views more  BMCBI 2008»
15 years 1 months ago
Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics
Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides...
Wiebke Timm, Alexandra Scherbart, Sebastian Bö...
ICS
2005
Tsinghua U.
15 years 7 months ago
What is worth learning from parallel workloads?: a user and session based analysis
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Julia Zilber, Ofer Amit, David Talby
BMCBI
2010
147views more  BMCBI 2010»
15 years 1 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
SIGCSE
2002
ACM
229views Education» more  SIGCSE 2002»
15 years 1 months ago
GraphicsMentor: a tool for learning graphics fundamentals
This paper discusses the functionality of GraphicsMentor. GraphicsMentor permits a student to modify many parameters of the camera, objects, and light sources interactively, and t...
Dejan Nikolic, Ching-Kuang Shene