Sciweavers

2100 search results - page 86 / 420
» Learning to rank on graphs
Sort
View
COLT
2008
Springer
15 years 8 months ago
An Efficient Reduction of Ranking to Classification
This paper describes an efficient reduction of the learning problem of ranking to binary classification. The reduction guarantees an average pairwise misranking regret of at most t...
Nir Ailon, Mehryar Mohri
KDD
2010
ACM
252views Data Mining» more  KDD 2010»
15 years 10 months ago
Fast query execution for retrieval models based on path-constrained random walks
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
Ni Lao, William W. Cohen
CIKM
2009
Springer
16 years 23 days ago
A general magnitude-preserving boosting algorithm for search ranking
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang...
ICALT
2003
IEEE
15 years 11 months ago
Using Gestures to Learn about Graphs: The Contribution of Multimodal Technology
This paper describes a study that investigates the use of a multimodal technology in a learning task. In relation to the recent interest in learning as a multimodal experience, th...
Stamatina Anastopoulou, Mike Sharples, Chris Baber
TNN
2010
127views Management» more  TNN 2010»
15 years 27 days ago
RAMOBoost: ranked minority oversampling in boosting
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
Sheng Chen, Haibo He, Edwardo A. Garcia