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» Learning Preferences with Hidden Common Cause Relations
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KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 5 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
AAMAS
2007
Springer
13 years 11 months ago
Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game
Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...
ICML
1998
IEEE
14 years 6 months ago
Heading in the Right Direction
Stochastic topological models, and hidden Markov models in particular, are a useful tool for robotic navigation and planning. In previous work we have shown how weak odometric dat...
Hagit Shatkay, Leslie Pack Kaelbling
DMIN
2007
183views Data Mining» more  DMIN 2007»
13 years 6 months ago
Crawling Attacks Against Web-based Recommender Systems
—User profiles derived from Web navigation data are used in important e-commerce applications such as Web personalization, recommender systems, and Web analytics. In the open en...
Runa Bhaumik, Robin D. Burke, Bamshad Mobasher
CVPR
2007
IEEE
14 years 7 months ago
Modeling Appearances with Low-Rank SVM
Several authors have noticed that the common representation of images as vectors is sub-optimal. The process of vectorization eliminates spatial relations between some of the near...
Lior Wolf, Hueihan Jhuang, Tamir Hazan