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» Listwise approach to learning to rank: theory and algorithm
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ICML
2008
IEEE
15 years 5 hour ago
Listwise approach to learning to rank: theory and algorithm
This paper aims to conduct a study on the listwise approach to learning to rank. The listwise approach learns a ranking function by taking individual lists as instances and minimi...
Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, Ha...
ICML
2009
IEEE
15 years 6 hour ago
Generalization analysis of listwise learning-to-rank algorithms
This paper presents a theoretical framework for ranking, and demonstrates how to perform generalization analysis of listwise ranking algorithms using the framework. Many learning-...
Yanyan Lan, Tie-Yan Liu, Zhiming Ma, Hang Li
RECSYS
2010
ACM
13 years 9 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
ICML
2007
IEEE
15 years 5 hour ago
Learning to rank: from pairwise approach to listwise approach
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...
WSDM
2010
ACM
211views Data Mining» more  WSDM 2010»
14 years 4 months ago
IntervalRank - Isotonic Regression with Listwise and Pairwise Constraints
Ranking a set of retrieved documents according to their relevance to a given query has become a popular problem at the intersection of web search, machine learning, and informatio...
Taesup Moon, Alex Smola, Yi Chang, Zhaohui Zheng