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EMNLP
2011
14 years 6 months ago
Training a Log-Linear Parser with Loss Functions via Softmax-Margin
Log-linear parsing models are often trained by optimizing likelihood, but we would prefer to optimise for a task-specific metric like Fmeasure. Softmax-margin is a convex objecti...
Michael Auli, Adam Lopez
GECCO
2000
Springer
123views Optimization» more  GECCO 2000»
15 years 10 months ago
Genomic computing: explanatory modelling for functional genomics
Many newly discovered genes are of unknown function. DNA microarrays are a method for determining the expression levels of all genes in an organism for which a complete genome seq...
Richard J. Gilbert, Jem J. Rowland, Douglas B. Kel...
ISBI
2002
IEEE
16 years 7 months ago
Automatic segmentation of mammographic masses using fuzzy shadow and maximum-likelihood analysis
This study attempted to accurately segment tumors in mammograms. Although this task is considered to be a preprocessing step in a computer analysis program, it plays an important ...
Lisa Kinnard, Shih-Chung Ben Lo, Paul C. Wang, Mat...
CC
2007
Springer
16 years 25 days ago
Preprocessing Strategy for Effective Modulo Scheduling on Multi-issue Digital Signal Processors
To achieve high resource utilization for multi-issue Digital Signal Processors (DSPs), production compilers commonly include variants of the iterative modulo scheduling algorithm. ...
Doosan Cho, Ravi Ayyagari, Gang-Ryung Uh, Yunheung...
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SENSYS
2005
ACM
16 years 7 days ago
Algorithms for generic role assignment in wireless sensor networks
We consider configuration of wireless sensor networks, where certain functions must be automatically assigned to sensor nodes, such that the properties of a sensor node (e.g., rem...
Christian Frank, Kay Römer