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COLT
2006
Springer
15 years 1 months ago
The Rademacher Complexity of Linear Transformation Classes
Bounds are given for the empirical and expected Rademacher complexity of classes of linear transformations from a Hilbert space H to a ...nite dimensional space. The results imply ...
Andreas Maurer
ML
2008
ACM
100views Machine Learning» more  ML 2008»
14 years 9 months ago
Convex multi-task feature learning
Andreas Argyriou, Theodoros Evgeniou, Massimiliano...
ICML
2008
IEEE
15 years 10 months ago
A unified architecture for natural language processing: deep neural networks with multitask learning
We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity...
Ronan Collobert, Jason Weston
SDM
2012
SIAM
322views Data Mining» more  SDM 2012»
13 years 3 days ago
Adaptive Multi-task Sparse Learning with an Application to fMRI Study
In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbo...
AUSAI
2008
Springer
14 years 11 months ago
Partial Order Hierarchical Reinforcement Learning
In this paper the notion of a partial-order plan is extended to task-hierarchies. We introduce the concept of a partial-order taskhierarchy that decomposes a problem using multi-ta...
Bernhard Hengst