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152
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JMLR
2010
144views more  JMLR 2010»
14 years 11 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
ICRA
2008
IEEE
169views Robotics» more  ICRA 2008»
15 years 11 months ago
Sparse incremental learning for interactive robot control policy estimation
— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
Daniel H. Grollman, Odest Chadwicke Jenkins
ESWS
2005
Springer
15 years 10 months ago
Semantic-Based Automated Composition of Distributed Learning Objects for Personalized E-Learning
Recent advances in e-learning techonologies and web services make realistic the idea that courseware for personalized e-learning can be built by dynamic composition of distributed ...
Simona Colucci, Tommaso Di Noia, Eugenio Di Sciasc...
AGENTS
2001
Springer
15 years 9 months ago
Using background knowledge to speed reinforcement learning in physical agents
This paper describes Icarus, an agent architecture that embeds a hierarchical reinforcement learning algorithm within a language for specifying agent behavior. An Icarus program e...
Daniel G. Shapiro, Pat Langley, Ross D. Shachter
140
Voted
IJCAI
2007
15 years 6 months ago
Maximum Margin Coresets for Active and Noise Tolerant Learning
We study the problem of learning large margin halfspaces in various settings using coresets to show that coresets are a widely applicable tool for large margin learning. A large m...
Sariel Har-Peled, Dan Roth, Dav Zimak