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» Speed, Accuracy, and Serial Order in Sequence Production
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AAAI
2011
12 years 5 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
BMCBI
2005
158views more  BMCBI 2005»
13 years 5 months ago
Automated generation of heuristics for biological sequence comparison
Background: Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. ...
Guy St. C. Slater, Ewan Birney
CVPR
2008
IEEE
14 years 7 months ago
Order consistent change detection via fast statistical significance testing
Robustness to illumination variations is a key requirement for the problem of change detection which in turn is a fundamental building block for many visual surveillance applicati...
Maneesh Singh, Vasu Parameswaran, Visvanathan Rame...
IPPS
2010
IEEE
13 years 3 months ago
Hybrid MPI/Pthreads parallelization of the RAxML phylogenetics code
Abstract--A hybrid MPI/Pthreads parallelization was implemented in the RAxML phylogenetics code. New MPI code was added to the existing Pthreads production code to exploit parallel...
Wayne Pfeiffer, Alexandros Stamatakis
LION
2010
Springer
209views Optimization» more  LION 2010»
13 years 10 months ago
Feature Extraction from Optimization Data via DataModeler's Ensemble Symbolic Regression
We demonstrate a means of knowledge discovery through feature extraction that exploits the search history of an optimization run. We regress a symbolic model ensemble from optimiza...
Kalyan Veeramachaneni, Katya Vladislavleva, Una-Ma...