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15 years 1 months ago
Towards a Systematics for Protein Subcellular Location: Quantitative Description of Protein Localization Patterns and Automated
Determination of the functions of all expressed proteins represents one of the major upcoming challenges in computational molecular biology. Since subcellular location plays a cru...
Robert F. Murphy, Michael V. Boland, Meel Velliste
CSMR
2010
IEEE
14 years 6 months ago
Does the Past Say It All? Using History to Predict Change Sets in a CMDB
To avoid unnecessary maintenance costs in large IT systems resulting from poorly planned changes, it is essential to manage and control changes to the system and to verify that all...
Sarah Nadi, Richard C. Holt, Serge Mankovski
AAAI
2011
13 years 12 months ago
Incorporating Boosted Regression Trees into Ecological Latent Variable Models
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Diet...
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 7 days ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
IJAR
2010
130views more  IJAR 2010»
14 years 10 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki