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ML
2010
ACM
124views Machine Learning» more  ML 2010»
15 years 2 months ago
Large scale image annotation: learning to rank with joint word-image embeddings
Image annotation datasets are becoming larger and larger, with tens of millions of images and tens of thousands of possible annotations. We propose a strongly performing method tha...
Jason Weston, Samy Bengio, Nicolas Usunier
ROBOCUP
2004
Springer
94views Robotics» more  ROBOCUP 2004»
15 years 9 months ago
Optic Flow Based Skill Learning for a Humanoid to Trap, Approach to, and Pass a Ball
Generation of a sequence of behaviors is necessary for the RoboCup Humanoid league to realize not simply a individual robot performance but also cooperative ones between robots. A ...
Masaki Ogino, Masaaki Kikuchi, Jun'ichiro Ooga, Ma...
ECML
2003
Springer
15 years 9 months ago
Pairwise Preference Learning and Ranking
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels (options). The training information consists of exampl...
Johannes Fürnkranz, Eyke Hüllermeier
AAAI
2008
15 years 6 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
COLT
2008
Springer
15 years 5 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál