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» Learning to rank on graphs
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MLG
2007
Springer
16 years 16 days ago
Graphs, Hypergraphs, and Inductive Logic Programming
Abstract. There are many connections between graph mining and inductive logic programming (ILP), or more generally relational learning. Up till now these connections have mostly be...
Hendrik Blockeel, Tijn Witsenburg, Joost N. Kok
BMVC
2010
15 years 4 months ago
Person Re-Identification by Support Vector Ranking
Solving the person re-identification problem involves matching observations of individuals across disjoint camera views. The problem becomes particularly hard in a busy public sce...
Bryan Prosser, Wei-Shi Zheng, Shaogang Gong, Tao X...
BMCBI
2010
186views more  BMCBI 2010»
15 years 6 months ago
Knowledge-based biomedical word sense disambiguation: comparison of approaches
Background: Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be u...
Antonio Jimeno Yepes, Alan R. Aronson
SIGIR
2012
ACM
13 years 8 months ago
Parallelizing ListNet training using spark
As ever-larger training sets for learning to rank are created, scalability of learning has become increasingly important to achieving continuing improvements in ranking accuracy [...
Shilpa Shukla, Matthew Lease, Ambuj Tewari
ICML
2004
IEEE
16 years 7 months ago
Generalized low rank approximations of matrices
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
Jieping Ye