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PROMISE
2010
13 years 2 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
OOPSLA
1998
Springer
14 years 1 days ago
Visualizing Dynamic Software System Information Through High-Level Models
Dynamic information collected as a software system executes can help software engineers perform some tasks on a system more effectively. To interpret the sizable amount of data ge...
Robert J. Walker, Gail C. Murphy, Bjørn N. ...
ICML
2005
IEEE
14 years 8 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers
BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Accelerated search for biomolecular network models to interpret high-throughput experimental data
Background: The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein e...
Suman Datta, Bahrad A. Sokhansanj
ICML
2009
IEEE
14 years 8 months ago
Structure learning with independent non-identically distributed data
There are well known algorithms for learning the structure of directed and undirected graphical models from data, but nearly all assume that the data consists of a single i.i.d. s...
Robert E. Tillman