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JMLR
2012
11 years 11 months ago
Perturbation based Large Margin Approach for Ranking
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
Eunho Yang, Ambuj Tewari, Pradeep D. Ravikumar
CVPR
2012
IEEE
11 years 11 months ago
Structured Local Predictors for image labelling
In this paper we introduce Structured Local Predictors (SLP) – A new formulation that considers the image labelling problem from a structured learning point of view. SLP are loc...
Samuel Rota Bulò, Peter Kontschieder, Marce...
GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
14 years 1 months ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague
ESANN
2001
13 years 10 months ago
Motor control and movement optimization learned by combining auto-imitative and genetic algorithms
In sensorimotor behaviour often a great movement execution variability is combined with a relatively low error in reaching the intended goal. This phenomenon can especially be obse...
Karl-Theodor Kalveram, Ulrich Nakte
COLT
2000
Springer
14 years 1 months ago
Entropy Numbers of Linear Function Classes
This paper collects together a miscellany of results originally motivated by the analysis of the generalization performance of the “maximum-margin” algorithm due to Vapnik and...
Robert C. Williamson, Alex J. Smola, Bernhard Sch&...