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» Information Theory, Inference, and Learning Algorithms
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BMCBI
2006
239views more  BMCBI 2006»
13 years 8 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
MM
2006
ACM
203views Multimedia» more  MM 2006»
14 years 2 months ago
Learning image manifolds by semantic subspace projection
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
Jie Yu, Qi Tian
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 8 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
CADE
2001
Springer
14 years 8 months ago
More On Implicit Syntax
Proof assistants based on type theories, such as Coq and Lego, allow users to omit subterms on input that can be inferred automatically. While those mechanisms are well known, ad-h...
Marko Luther
WEBDB
2010
Springer
178views Database» more  WEBDB 2010»
14 years 1 months ago
Using Latent-Structure to Detect Objects on the Web
An important requirement for emerging applications which aim to locate and integrate content distributed over the Web is to identify pages that are relevant for a given domain or ...
Luciano Barbosa, Juliana Freire