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» On learning with dissimilarity functions
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CVPR
2009
IEEE
16 years 1 months ago
Learning multi-modal densities on Discriminative Temporal Interaction Manifold for group activity recognition
While video-based activity analysis and recognition has received much attention, existing body of work mostly deals with single object/person case. Coordinated multi-object activi...
Ruonan Li, Rama Chellappa, Shaohua Kevin Zhou
181
Voted
SC
2009
ACM
16 years 1 months ago
Lessons learned from a year's worth of benchmarks of large data clouds
In this paper, we discuss some of the lessons that we have learned working with the Hadoop and Sector/Sphere systems. Both of these systems are cloud-based systems designed to sup...
Yunhong Gu, Robert L. Grossman
IROS
2009
IEEE
205views Robotics» more  IROS 2009»
16 years 1 months ago
Model-based and learned semantic object labeling in 3D point cloud maps of kitchen environments
Abstract— We report on our experiences regarding the acquisition of hybrid Semantic 3D Object Maps for indoor household environments, in particular kitchens, out of sensed 3D poi...
Radu Bogdan Rusu, Zoltan Csaba Marton, Nico Blodow...
CCGRID
2008
IEEE
16 years 1 months ago
Grid Differentiated Services: A Reinforcement Learning Approach
—Large scale production grids are a major case for autonomic computing. Following the classical definition of Kephart, an autonomic computing system should optimize its own beha...
Julien Perez, Cécile Germain-Renaud, Bal&aa...
ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
16 years 1 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...