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» Online Learning of Approximate Dependency Parsing Algorithms
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NIPS
2008
13 years 9 months ago
Modeling the effects of memory on human online sentence processing with particle filters
Language comprehension in humans is significantly constrained by memory, yet rapid, highly incremental, and capable of utilizing a wide range of contextual information to resolve ...
Roger P. Levy, Florencia Reali, Thomas L. Griffith...
ICML
2007
IEEE
14 years 8 months ago
Exponentiated gradient algorithms for log-linear structured prediction
Conditional log-linear models are a commonly used method for structured prediction. Efficient learning of parameters in these models is therefore an important problem. This paper ...
Amir Globerson, Terry Koo, Xavier Carreras, Michae...
COLT
2008
Springer
13 years 9 months ago
Linear Algorithms for Online Multitask Classification
We design and analyze interacting online algorithms for multitask classification that perform better than independent learners whenever the tasks are related in a certain sense. W...
Giovanni Cavallanti, Nicolò Cesa-Bianchi, C...
NIPS
1994
13 years 9 months ago
On-line Learning of Dichotomies
The performance of on-line algorithms for learning dichotomies is studied. In on-line learning, the number of examples P is equivalent to the learning time, since each example is ...
N. Barkai, H. Sebastian Seung, Haim Sompolinsky
KR
1992
Springer
13 years 11 months ago
Learning Useful Horn Approximations
While the task of answering queries from an arbitrary propositional theory is intractable in general, it can typicallybe performed e ciently if the theory is Horn. This suggests t...
Russell Greiner, Dale Schuurmans