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» Preference elicitation with subjective features
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KDD
2009
ACM
229views Data Mining» more  KDD 2009»
14 years 6 months ago
Relational learning via latent social dimensions
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
Lei Tang, Huan Liu
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 6 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 6 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
IROS
2008
IEEE
137views Robotics» more  IROS 2008»
14 years 17 days ago
Universal web interfaces for robot control frameworks
— Developers and end-users have to interface robotic systems for control and feedback. Such systems are typically co-engineered with their graphical user interfaces. In the past,...
Jan Koch, Max Reichardt, Karsten Berns
SIGIR
2006
ACM
14 years 3 days ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi