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NIPS
2003
15 years 6 months ago
Policy Search by Dynamic Programming
We consider the policy search approach to reinforcement learning. We show that if a “baseline distribution” is given (indicating roughly how often we expect a good policy to v...
J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng, Jeff...
190
Voted
SIGIR
2012
ACM
13 years 7 months ago
Learning to suggest: a machine learning framework for ranking query suggestions
We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre...
141
Voted
ICML
1997
IEEE
16 years 5 months ago
Learning Belief Networks in the Presence of Missing Values and Hidden Variables
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...
Nir Friedman
ECTEL
2008
Springer
15 years 6 months ago
Evaluating Spatial Knowledge through Problem-Solving in Virtual Learning Environments
Modeling the cognitive processes of learners is fundamental to build educational software that are autonomous and that can provide highly tailored assistance during learning [3]. F...
Philippe Fournier-Viger, Roger Nkambou, Andr&eacut...
147
Voted
IJCAI
2003
15 years 6 months ago
Qualitative Map Learning Based on Co-visibility of Objects
This paper proposes a unique map learning method for mobile robots based on the co-visibility infor­ mation of objects i.e., the information on whether two objects are visible at...
Takehisa Yairi, Koichi Hori