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ACL
2006
13 years 11 months ago
Semantic Parsing with Structured SVM Ensemble Classification Models
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...
Minh Le Nguyen, Akira Shimazu, Xuan Hieu Phan
SDM
2004
SIAM
189views Data Mining» more  SDM 2004»
13 years 11 months ago
An Abstract Weighting Framework for Clustering Algorithms
act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
Richard Nock, Frank Nielsen
DSS
2008
104views more  DSS 2008»
13 years 10 months ago
A support system for predicting eBay end prices
We create a support system for predicting end prices on eBay. The end price predictions are based on the item descriptions found in the item listings of eBay, and on some numerica...
Dennis van Heijst, Rob Potharst, Michiel C. van We...
PAMI
2008
175views more  PAMI 2008»
13 years 10 months ago
Discriminative Feature Co-Occurrence Selection for Object Detection
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Takeshi Mita, Toshimitsu Kaneko, Björn Stenge...
TKDE
2008
123views more  TKDE 2008»
13 years 9 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko