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» Machine Learning by Function Decomposition
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ICML
2005
IEEE
16 years 2 months ago
Supervised clustering with support vector machines
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
Thomas Finley, Thorsten Joachims
BMCBI
2010
154views more  BMCBI 2010»
15 years 1 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
BMCBI
2011
14 years 8 months ago
DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning
Background: Accurate identification of protein domain boundaries is useful for protein structure determination and prediction. However, predicting protein domain boundaries from a...
Jesse Eickholt, Xin Deng, Jianlin Cheng
MICRO
2008
IEEE
148views Hardware» more  MICRO 2008»
15 years 8 months ago
Coordinated management of multiple interacting resources in chip multiprocessors: A machine learning approach
—Efficient sharing of system resources is critical to obtaining high utilization and enforcing system-level performance objectives on chip multiprocessors (CMPs). Although sever...
Ramazan Bitirgen, Engin Ipek, José F. Mart&...
AIME
1997
Springer
15 years 5 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....