Sciweavers

Share
warning: Creating default object from empty value in /var/www/modules/taxonomy/taxonomy.module on line 1416.
ESSLLI
2009
Springer
9 years 11 months ago
Variable Selection in Logistic Regression: The British English Dative Alternation
This paper addresses the problem of selecting the `optimal' variable subset in a logistic regression model for a medium-sized data set. As a case study, we take the British En...
Daphne Theijssen
NAACL
2010
9 years 11 months ago
Good Question! Statistical Ranking for Question Generation
We address the challenge of automatically generating questions from reading materials for educational practice and assessment. Our approach is to overgenerate questions, then rank...
Michael Heilman, Noah A. Smith
CSDA
2006
304views more  CSDA 2006»
10 years 1 months ago
Using principal components for estimating logistic regression with high-dimensional multicollinear data
The logistic regression model is used to predict a binary response variable in terms of a set of explicative ones. The estimation of the model parameters is not too accurate and t...
Ana M. Aguilera, Manuel Escabias, Mariano J. Valde...
IJCAI
2007
10 years 2 months ago
Logistic Regression Models for a Fast CBIR Method Based on Feature Selection
Distance measures like the Euclidean distance have been the most widely used to measure similarities between feature vectors in the content-based image retrieval (CBIR) systems. H...
Riadh Ksantini, Djemel Ziou, Bernard Colin, Fran&c...
CEAS
2005
Springer
10 years 6 months ago
Reply Expectation Prediction for Email Management
We reduce email overload by addressing the problem of waiting for a reply to one’s email. We predict whether sent and received emails necessitate a reply, enabling the user to b...
Mark Dredze, John Blitzer, Fernando Pereira
SIGIR
2006
ACM
10 years 7 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
ICPR
2008
IEEE
10 years 7 months ago
Fast multiple instance learning via L1, 2 logistic regression
In this paper, we develop an efficient logistic regression model for multiple instance learning that combines L1 and L2 regularisation techniques. An L1 regularised logistic regr...
Zhouyu Fu, Antonio Robles-Kelly
WWW
2008
ACM
11 years 2 months ago
Contextual advertising by combining relevance with click feedback
Contextual advertising supports much of the Web's ecosystem today. User experience and revenue (shared by the site publisher ad the ad network) depend on the relevance of the...
Deepayan Chakrabarti, Deepak Agarwal, Vanja Josifo...
ICML
2007
IEEE
11 years 2 months ago
Trust region Newton methods for large-scale logistic regression
Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method t...
Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi
books