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COLT
2006
Springer
13 years 11 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»
13 years 7 months ago
Convex multi-task feature learning
Andreas Argyriou, Theodoros Evgeniou, Massimiliano...
ICML
2008
IEEE
14 years 8 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»
11 years 10 months 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
13 years 9 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