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ML
2010
ACM
124views Machine Learning» more  ML 2010»
15 years 15 hour 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
CIDM
2007
IEEE
15 years 5 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
ALT
1998
Springer
15 years 5 months ago
Predictive Learning Models for Concept Drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the con...
John Case, Sanjay Jain, Susanne Kaufmann, Arun Sha...
ICML
2009
IEEE
16 years 2 months ago
Polyhedral outer approximations with application to natural language parsing
Recent approaches to learning structured predictors often require approximate inference for tractability; yet its effects on the learned model are unclear. Meanwhile, most learnin...
André F. T. Martins, Noah A. Smith, Eric P....
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
15 years 2 months ago
Experiments with indexed FOR-loops in genetic programming
We investigated how indexed FOR-loops, such as the ones found in procedural programming languages, can be implemented in genetic programming. We use them to train programs that le...
Gayan Wijesinghe, Victor Ciesielski