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FOCS
1990
IEEE
15 years 8 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
CIKM
2008
Springer
15 years 6 months ago
Learning the distance metric in a personal ontology
Personal ontology construction is the task of sorting through relevant materials, identifying the main topics and concepts, and organizing them to suit personal needs. Automatic c...
Hui Yang, Jamie Callan
COLT
2007
Springer
15 years 10 months ago
U-Shaped, Iterative, and Iterative-with-Counter Learning
This paper solves an important problem left open in the literature by showing that U-shapes are unnecessary in iterative learning. A U-shape occurs when a learner first learns, t...
John Case, Samuel E. Moelius
CVPR
2008
IEEE
16 years 6 months ago
Face alignment via boosted ranking model
Face alignment seeks to deform a face model to match it with the features of the image of a face by optimizing an appropriate cost function. We propose a new face model that is al...
Gianfranco Doretto, Hao Wu, Xiaoming Liu 0002
ICML
2006
IEEE
16 years 5 months ago
Combining discriminative features to infer complex trajectories
We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
David A. Ross, Simon Osindero, Richard S. Zemel