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» Learning from Highly Structured Data by Decomposition
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JAIR
2010
131views more  JAIR 2010»
15 years 2 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
RSS
2007
152views Robotics» more  RSS 2007»
15 years 5 months ago
Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
IWDC
2001
Springer
15 years 8 months ago
Design and Deployment of a Passive Monitoring Infrastructure
Abstract— This paper presents the architecture of a passive monitoring system installed within the Sprint IP backbone network. This system differs from other packet monitoring sy...
Chuck Fraleigh, Christophe Diot, Bryan Lyles, Sue ...
AIED
2007
Springer
15 years 10 months ago
Assessing Learning in a Peer-Driven Tutoring System
In many intelligent tutoring systems, a detailed model of the task domain is constructed and used to provide students with assistance and direction. Reciprocal tutoring systems, h...
Ari Bader-Natal, Jordan B. Pollack
CIVR
2008
Springer
271views Image Analysis» more  CIVR 2008»
15 years 5 months ago
Multiple feature fusion by subspace learning
Since the emergence of extensive multimedia data, feature fusion has been more and more important for image and video retrieval, indexing and annotation. Existing feature fusion t...
Yun Fu, Liangliang Cao, Guodong Guo, Thomas S. Hua...