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» The Lookahead Principle for Preference Elicitation: Experime...
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IJCAI
2007
13 years 10 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
EOR
2011
140views more  EOR 2011»
13 years 1 days ago
Compact bidding languages and supplier selection for markets with economies of scale and scope
Combinatorial auctions have been used in procurement markets with economies of scope. Preference elicitation is already a problem in single-unit combinatorial auctions, but it bec...
Martin Bichler, Stefan Schneider, Kemal Guler, Meh...
SIGIR
2010
ACM
14 years 13 days ago
Learning more powerful test statistics for click-based retrieval evaluation
Interleaving experiments are an attractive methodology for evaluating retrieval functions through implicit feedback. Designed as a blind and unbiased test for eliciting a preferen...
Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, T...
ICIP
2010
IEEE
13 years 6 months ago
Automatic production of personalized basketball video summaries from multi-sensored data
We propose a flexible framework for producing highly personalized basketball video summaries, by intergrating contextural information, narrative user preferences on story pattern,...
Fan Chen, Christophe De Vleeschouwer
UIST
2010
ACM
13 years 6 months ago
Tag expression: tagging with feeling
In this paper we introduce tag expression, a novel form of preference elicitation that combines elements from tagging and rating systems. Tag expression enables users to apply aff...
Jesse Vig, Matthew Soukup, Shilad Sen, John Riedl