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ATAL
2009
Springer
15 years 10 months ago
Learning whom to trust: using graphical models for learning about information providers
Philip Hendrix, Ya'akov Gal, Avi Pfeffer
ICML
2004
IEEE
16 years 4 months ago
Relational sequential inference with reliable observations
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...
Alan Fern, Robert Givan
195
Voted
ADVCS
2011
251views Database» more  ADVCS 2011»
14 years 3 months ago
Emergent Social Learning Networks in Organizations with Heterogeneous Agents
Two distinct learning mechanisms are considered for a population of agents who engage in decentralized search for the common optimum. An agent may choose to learn via innovation (...
Myong-Hun Chang
CORR
2000
Springer
92views Education» more  CORR 2000»
15 years 3 months ago
Predicting the expected behavior of agents that learn about agents: the CLRI framework
We describe a framework and equations used to model and predict the behavior of multi-agent systems (MASs) with learning agents. A difference equation is used for calculating the ...
José M. Vidal, Edmund H. Durfee
146
Voted
NIPS
2008
15 years 4 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang