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CVPR
2007
IEEE
14 years 10 months ago
Learning Color Names from Real-World Images
Within a computer vision context color naming is the action of assigning linguistic color labels to image pixels. In general, research on color naming applies the following paradi...
Joost van de Weijer, Cordelia Schmid, Jakob J. Ver...
ICML
2005
IEEE
14 years 9 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven
CHI
2007
ACM
14 years 8 months ago
Dynamic detection of novice vs. skilled use without a task model
If applications were able to detect a user's expertise, then software could automatically adapt to better match expertise. Detecting expertise is difficult because a user...
Amy Hurst, Scott E. Hudson, Jennifer Mankoff
CIDM
2009
IEEE
14 years 2 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
GECCO
2009
Springer
141views Optimization» more  GECCO 2009»
14 years 2 months ago
Distributed hyper-heuristics for real parameter optimization
Hyper-heuristics (HHs) are heuristics that work with an arbitrary set of search operators or algorithms and combine these algorithms adaptively to achieve a better performance tha...
Marco Biazzini, Balázs Bánhelyi, Alb...