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ICML
2007
IEEE
16 years 7 months ago
Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
Kai Ni, Lawrence Carin, David B. Dunson
ECML
2004
Springer
16 years 3 days ago
Fisher Kernels for Logical Sequences
One approach to improve the accuracy of classifications based on generative models is to combine them with successful discriminative algorithms. Fisher kernels were developed to c...
Kristian Kersting, Thomas Gärtner
ATAL
2007
Springer
15 years 10 months ago
Interactive dynamic influence diagrams
This paper extends the framework of dynamic influence diagrams (DIDs) to the multi-agent setting. DIDs are computational representations of the Partially Observable Markov Decisio...
Kyle Polich, Piotr J. Gmytrasiewicz
ATAL
2006
Springer
15 years 10 months ago
Learning executable agent behaviors from observation
We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we ...
Andrew Guillory, Hai Nguyen, Tucker R. Balch, Char...
ICML
2004
IEEE
16 years 7 months ago
Learning low dimensional predictive representations
Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...