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» Learning to Track with Multiple Observers
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UAI
2001
13 years 9 months ago
Learning the Dimensionality of Hidden Variables
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. Dete...
Gal Elidan, Nir Friedman
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 8 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
HUC
2010
Springer
13 years 8 months ago
Tasking networked CCTV cameras and mobile phones to identify and localize multiple people
We present a method to identify and localize people by leveraging existing CCTV camera infrastructure along with inertial sensors (accelerometer and magnetometer) within each pers...
Thiago Teixeira, Deokwoo Jung, Andreas Savvides
ISER
2000
Springer
133views Robotics» more  ISER 2000»
13 years 11 months ago
Merging Gaussian Distributions for Object Localization in Multi-robot Systems
: We present a method for representing, communicating, and fusing distributed, noisy, and uncertain observations of an object by multiple robots. The approach relies on re-paramete...
Ashley W. Stroupe, Martin C. Martin, Tucker R. Bal...
ICML
1999
IEEE
14 years 8 months ago
Implicit Imitation in Multiagent Reinforcement Learning
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
Bob Price, Craig Boutilier