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» Learning to rank on graphs
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PDP
2006
IEEE
15 years 3 months ago
Parallel Adaptive Technique for Computing PageRank
Re-ranking the search results using PageRank is a well-known technique used in modern search engines. Running an iterative algorithm like PageRank on a large web graph consumes bo...
Arnon Rungsawang, Bundit Manaskasemsak
KDD
2010
ACM
257views Data Mining» more  KDD 2010»
15 years 1 months ago
Multi-task learning for boosting with application to web search ranking
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
CIKM
2005
Springer
15 years 3 months ago
MailRank: using ranking for spam detection
Can we use social networks to combat spam? This paper investigates the feasibility of MailRank, a new email ranking and classification scheme exploiting the social communication ...
Paul-Alexandru Chirita, Jörg Diederich, Wolfg...
ICML
2010
IEEE
14 years 10 months ago
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, His...
WWW
2010
ACM
15 years 4 months ago
Factorizing personalized Markov chains for next-basket recommendation
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...