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» Learning on the Test Data: Leveraging Unseen Features
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PPSN
2010
Springer
13 years 7 months ago
Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...
CIKM
2009
Springer
14 years 3 months ago
Large margin transductive transfer learning
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
Brian Quanz, Jun Huan
EMNLP
2009
13 years 6 months ago
Mining Search Engine Clickthrough Log for Matching N-gram Features
User clicks on a URL in response to a query are extremely useful predictors of the URL's relevance to that query. Exact match click features tend to suffer from severe data s...
Huihsin Tseng, Longbin Chen, Fan Li, Ziming Zhuang...
JAIR
2006
137views more  JAIR 2006»
13 years 9 months ago
Learning Sentence-internal Temporal Relations
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
Maria Lapata, Alex Lascarides
MVA
2007
114views Computer Vision» more  MVA 2007»
13 years 10 months ago
Sign Language Recognition Using Boosted Volumetric Features
This paper proposes a method for sign language recognition that bypasses the need for tracking by classifying the motion directly. The method uses the natural extension of haar li...
Helen Cooper, Richard Bowden