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NLE
2008
140views more  NLE 2008»
15 years 6 months ago
Active learning and logarithmic opinion pools for HPSG parse selection
For complex tasks such as parse selection, the creation of labelled training sets can be extremely costly. Resource-efficient schemes for creating informative labelled material mu...
Jason Baldridge, Miles Osborne
SEMWEB
2001
Springer
15 years 11 months ago
OntoMap - the Guide to the Upper-Level
Abstract. The upper-level ontologies are theories that capture the most common concepts, which are relevant for many of the tasks involving knowledge extraction, representation, an...
Atanas K. Kirakov, Marin Dimitrov
ICALT
2007
IEEE
16 years 1 months ago
Bayesian Modelling of Confusability of Phoneme-Grapheme Connections
Deficiencies in the ability to map letters to sounds are currently considered to be the most likely early signs of dyslexia [4]. This has motivated the use of Literate, a compute...
Mikko Vilenius, Janne V. Kujala, Ulla Richardson, ...
CORR
2010
Springer
96views Education» more  CORR 2010»
15 years 7 months ago
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive threshol...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
AAAI
2007
15 years 9 months ago
Measuring the Level of Transfer Learning by an AP Physics Problem-Solver
Transfer learning is the ability of an agent to apply knowledge learned in previous tasks to new problems or domains. We approach this problem by focusing on model formulation, i....
Matthew Klenk, Kenneth D. Forbus