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ICML
2008
IEEE
16 years 7 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
BMCBI
2004
123views more  BMCBI 2004»
15 years 6 months ago
Interaction profile-based protein classification of death domain
Background: The increasing number of protein sequences and 3D structure obtained from genomic initiatives is leading many of us to focus on proteomics, and to dedicate our experim...
Drew Lett, Michael Hsing, Frederic Pio
ICMLA
2010
15 years 4 months ago
Heuristic Method for Discriminative Structure Learning of Markov Logic Networks
Markov Logic Networks (MLNs) combine Markov Networks and first-order logic by attaching weights to firstorder formulas and viewing them as templates for features of Markov Networks...
Quang-Thang Dinh, Matthieu Exbrayat, Christel Vrai...
AIEDU
2008
162views more  AIEDU 2008»
15 years 6 months ago
Designing Learning by Teaching Agents: The Betty's Brain System
The idea that teaching others is a powerful way to learn is intuitively compelling and supported in the research literature. We have developed computer-based, domain-independent Te...
Krittaya Leelawong, Gautam Biswas
IJCAI
2007
15 years 7 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...