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» Learning Preferences for Multiclass Problems
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UAI
2003
13 years 10 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...

Publication
240views
12 years 7 months ago
Bayesian multitask inverse reinforcement learning
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Christos Dimitrakakis, Constantin A. Rothkopf
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
ICML
2009
IEEE
14 years 9 months ago
Online feature elicitation in interactive optimization
Most models of utility elicitation in decision support and interactive optimization assume a predefined set of "catalog" features over which user preferences are express...
Craig Boutilier, Kevin Regan, Paolo Viappiani
ADMA
2006
Springer
167views Data Mining» more  ADMA 2006»
14 years 3 months ago
A Correlation Approach for Automatic Image Annotation
The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...
David R. Hardoon, Craig Saunders, Sándor Sz...