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ICML
1999
IEEE
16 years 7 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
COLT
2007
Springer
16 years 1 months ago
Property Testing: A Learning Theory Perspective
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is li...
Dana Ron
GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
15 years 10 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson
CEEMAS
2005
Springer
16 years 9 days ago
Case-Based Student Modeling in Multi-agent Learning Environment
Abstract. The student modeling (SM) is a core component in the development of Intelligent Learning Environments (ILEs). In this paper we describe how a Multi-agent Intelligent Lear...
Carolina González, Juan C. Burguillo-Rial, ...
IJSI
2008
156views more  IJSI 2008»
15 years 6 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker