Sciweavers

86 search results - page 9 / 18
» Exploiting Context When Learning to Classify
Sort
View
KCAP
2011
ACM
12 years 10 months ago
Eliciting hierarchical structures from enumerative structures for ontology learning
Some discourse structures such as enumerative structures have typographical, punctuational and laying out characteristics which (1) make them easily identifiable and (2) convey hi...
Mouna Kamel, Bernard Rothenburger
JMLR
2010
146views more  JMLR 2010»
13 years 2 months ago
Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking
The success of simple methods for classification shows that is is often not necessary to model complex attribute interactions to obtain good classification accuracy on practical p...
Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhar...
CVPR
2004
IEEE
14 years 9 months ago
Gibbs Likelihoods for Bayesian Tracking
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Stefan Roth, Leonid Sigal, Michael J. Black
EDM
2008
93views Data Mining» more  EDM 2008»
13 years 9 months ago
A Preliminary Analysis of the Logged Questions that Students Ask in Introductory Computer Science
Asking questions is widely believed to contribute to student learning, but little is known about the questions that students ask or how to exploit them in tutorial interventions to...
Cecily Heiner
AAAI
2004
13 years 9 months ago
Learning and Applying Competitive Strategies
Learning reusable sequences can support the development of expertise in many domains, either by improving decisionmaking quality or decreasing execution speed. This paper introduc...
Esther Lock, Susan L. Epstein