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» Using Problems to Learn Service-Oriented Computing
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BMCBI
2007
157views more  BMCBI 2007»
15 years 2 months ago
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...
Nico Pfeifer, Andreas Leinenbach, Christian G. Hub...
126
Voted
CONEXT
2010
ACM
15 years 11 days ago
NEVERMIND, the problem is already fixed: proactively detecting and troubleshooting customer DSL problems
Traditional DSL troubleshooting solutions are reactive, relying mainly on customers to report problems, and tend to be labor-intensive, time consuming, prone to incorrect resoluti...
Yu Jin, Nick G. Duffield, Alexandre Gerber, Patric...
162
Voted
NCA
2008
IEEE
15 years 2 months ago
Neurodynamic programming: a case study of the traveling salesman problem
The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal differenc...
Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong ...
CSEE
2007
Springer
15 years 8 months ago
Increased Retention of Early Computer Science and Software Engineering Students Using Pair Programming
An important problem faced by many Computer Science and Software Engineering programs is declining enrollment. In an effort to reverse that trend at Mississippi State University, ...
Jeffrey C. Carver, Lisa Henderson, Lulu He, Julia ...
CEC
2005
IEEE
15 years 4 months ago
XCS with computed prediction in continuous multistep environments
We apply XCS with computed prediction (XCSF) to tackle multistep reinforcement learning problems involving continuous inputs. In essence we use XCSF as a method of generalized rein...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...