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» Optimizing Complex Loss Functions in Structured Prediction
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TIP
2011
123views more  TIP 2011»
14 years 4 months ago
Spatial Sparsity-Induced Prediction (SIP) for Images and Video: A Simple Way to Reject Structured Interference
We propose a prediction technique that is geared toward forming successful estimates of a signal based on a correlated anchor signal that is contaminated with complex interference...
Gang Hua, Onur G. Guleryuz
BMCBI
2010
156views more  BMCBI 2010»
14 years 9 months ago
Mathematical model for empirically optimizing large scale production of soluble protein domains
Background: Efficient dissection of large proteins into their structural domains is critical for high throughput proteome analysis. So far, no study has focused on mathematically ...
Eisuke Chikayama, Atsushi Kurotani, Takanori Tanak...
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ACL
2006
14 years 11 months ago
Minimum Risk Annealing for Training Log-Linear Models
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
David A. Smith, Jason Eisner
PPSN
1994
Springer
15 years 1 months ago
A Cooperative Coevolutionary Approach to Function Optimization
A general model for the coevolution of cooperating species is presented. This model is instantiated and tested in the domain of function optimization, and compared with a tradition...
Mitchell A. Potter, Kenneth A. De Jong
BMCBI
2011
14 years 4 months ago
Predicting functionally important SNP classes based on negative selection
Background: With the advent of cost-effective genotyping technologies, genome-wide association studies allow researchers to examine hundreds of thousands of single nucleotide poly...
Mark A. Levenstien, Robert J. Klein