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118
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ECML
2007
Springer
15 years 8 months ago
Learning from Relevant Tasks Only
We extend our recent work on relevant subtask learning, a new variant of multitask learning where the goal is to learn a good classifier for a task-of-interest with too few train...
Samuel Kaski, Jaakko Peltonen
126
Voted
APIN
2002
90views more  APIN 2002»
15 years 2 months ago
Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning
Abstract: Locally weighted learning (LWL) is a class of techniques from nonparametric statistics that provides useful representations and training algorithms for learning about com...
Stefan Schaal, Christopher G. Atkeson, Sethu Vijay...
137
Voted
AI
2011
Springer
14 years 6 months ago
Learning Dialogue POMDP Models from Data
In this paper, we learn the components of dialogue POMDP models from data. In particular, we learn the states, observations, as well as transition and observation functions based o...
Hamid R. Chinaei, Brahim Chaib-draa
132
Voted
IUI
2009
ACM
15 years 11 months ago
From geek to sleek: integrating task learning tools to support end users in real-world applications
Numerous techniques exist to help users automate repetitive tasks; however, none of these methods fully support enduser creation, use, and modification of the learned tasks. We pr...
Aaron Spaulding, Jim Blythe, Will Haines, Melinda ...
124
Voted
AIED
2009
Springer
15 years 9 months ago
Looking Into Collaborative Learning: Design from Macro- and Micro-Script Perspectives
Design of collaborative learning (CL) scenarios is a complex task, but necessary if the goal of the collaboration is learning. Creating well-thought-out CL scenarios requires exper...
Eloy D. Villasclaras-Fernández, Seiji Isota...