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ICML
2009
IEEE
16 years 20 days ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
FOIKS
2008
Springer
15 years 8 months ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn
BMCBI
2006
118views more  BMCBI 2006»
14 years 12 months ago
Automatic generation of gene finders for eukaryotic species
Background: The number of sequenced eukaryotic genomes is rapidly increasing. This means that over time it will be hard to keep supplying customised gene finders for each genome. ...
Kasper Munch, Anders Krogh
VISUALIZATION
1997
IEEE
15 years 4 months ago
ROAMing terrain: real-time optimally adapting meshes
Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and ground-based aircraf...
Mark A. Duchaineau, Murray Wolinsky, David E. Sige...
CJ
1999
126views more  CJ 1999»
14 years 11 months ago
Source Level Static Branch Prediction
The ability to predict the directions of branches, especially conditional branches, is an important problem in modern computer architecture and advanced compilers. Many static and...
W. F. Wong