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» Effective Prediction and its Computational Complexity
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ICMLA
2008
13 years 7 months ago
Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
Jun Won Lee, Christophe G. Giraud-Carrier
SC
1991
ACM
13 years 9 months ago
Delayed consistency and its effects on the miss rate of parallel programs
In cache based multiprocessors a protocol must maintain coherence among replicated copies of shared writable data. In delayed consistency protocols the effect of out-going and in-...
Michel Dubois, Jin-Chin Wang, Luiz André Ba...
HPCA
2003
IEEE
14 years 6 months ago
Dynamic Data Dependence Tracking and its Application to Branch Prediction
To continue to improve processor performance, microarchitects seek to increase the effective instruction level parallelism (ILP) that can be exploited in applications. A fundament...
Lei Chen, Steve Dropsho, David H. Albonesi
BMCBI
2010
105views more  BMCBI 2010»
13 years 6 months ago
A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction
Background: Current scoring functions are not very successful in protein-ligand binding affinity prediction albeit their popularity in structure-based drug designs. Here, we propo...
Tiejun Cheng, Zhihai Liu, Renxiao Wang
RECOMB
2010
Springer
13 years 7 months ago
An Algorithmic Framework for Predicting Side-Effects of Drugs
Abstract. One of the critical stages in drug development is the identification of potential side effects for promising drug leads. Large scale clinical experiments aimed at discove...
Nir Atias, Roded Sharan