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BMCBI
2004
158views more  BMCBI 2004»
15 years 6 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
NIPS
2007
15 years 7 months ago
Gaussian Process Models for Link Analysis and Transfer Learning
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
Kai Yu, Wei Chu
IWC
2008
99views more  IWC 2008»
15 years 6 months ago
Pedagogy and usability in interactive algorithm visualizations: Designing and evaluating CIspace
Interactive algorithm visualizations (AVs) are powerful tools for teaching and learning concepts that are difficult to describe with static media alone. However, while countless A...
Saleema Amershi, Giuseppe Carenini, Cristina Conat...
CORR
2000
Springer
120views Education» more  CORR 2000»
15 years 6 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
ACML
2009
Springer
15 years 10 months ago
Learning Algorithms for Domain Adaptation
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
Manas A. Pathak, Eric Nyberg