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» Learning to Rank Using an Ensemble of Lambda-Gradient Models
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WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 5 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
MANSCI
2006
121views more  MANSCI 2006»
13 years 7 months ago
Methodologies and Algorithms for Group-Rankings Decision
The problem of group ranking, a.k.a. rank aggregation, has been studied in contexts varying from sports, to multi-criteria decision making, to machine learning, to ranking web pag...
Dorit S. Hochbaum, Asaf Levin
JMLR
2006
145views more  JMLR 2006»
13 years 7 months ago
Ensemble Pruning Via Semi-definite Programming
An ensemble is a group of learning models that jointly solve a problem. However, the ensembles generated by existing techniques are sometimes unnecessarily large, which can lead t...
Yi Zhang 0006, Samuel Burer, W. Nick Street
IJCAI
2003
13 years 9 months ago
A Learning Algorithm for Web Page Scoring Systems
Hyperlink analysis is a successful approach to define algorithms which compute the relevance of a document on the basis of the citation graph. In this paper we propose a technique...
Michelangelo Diligenti, Marco Gori, Marco Maggini
UAI
2003
13 years 9 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...