BMCBI
2008
14 years 17 days ago
2008
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
ISCAPDCS
2001
14 years 1 months ago
2001
-Multi-dimensional applications, such as image processing and seismic analysis, usually require the optimized performance obtained from instruction-level parallelism. The critical ...
DAGSTUHL
2006
14 years 1 months ago
2006
The results of recent studies on prediction markets are encouraging. Prior experience demonstrates that markets with different incentive schemes predicted uncertain future events ...
USENIX
2008
14 years 2 months ago
2008
Conventional prefetching schemes regard prediction accuracy as important because useless data prefetched by a faulty prediction may pollute the cache. If prefetching requires cons...
CGO
2006
IEEE
14 years 4 months ago
2006
IEEE
Static compilers use profiling to predict run-time program behavior. Generally, this requires multiple input sets to capture wide variations in run-time behavior. This is expensiv...
ISCA
1998
IEEE
14 years 4 months ago
1998
IEEE
As the issue rate and depth of pipelining of high performance Superscalar processors increase, the importance of an excellent branch predictor becomes more vital to delivering the...
EUROPAR
1999
Springer
14 years 4 months ago
1999
Springer
Two-level predictors deliver highly accurate conditional branch prediction, indirect branch target prediction and value prediction. Accurate prediction enables speculative executio...
CSMR
2009
IEEE
14 years 5 months ago
2009
IEEE
There is an increasing interest in more accurate prediction of software maintainability in order to better manage and control software maintenance. Recently, TreeNet has been prop...
PLDI
2003
ACM
14 years 5 months ago
2003
ACM
Interpreters designed for efficiency execute a huge number of indirect branches and can spend more than half of the execution time in indirect branch mispredictions. Branch target...
ECML
2005
Springer
14 years 6 months ago
2005
Springer
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...