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» Learning to Track with Multiple Observers
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TSMC
2008
132views more  TSMC 2008»
13 years 7 months ago
Ensemble Algorithms in Reinforcement Learning
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Marco A. Wiering, Hado van Hasselt
ICCV
2001
IEEE
14 years 9 months ago
Human Tracking with Mixtures of Trees
Tree-structured probabilistic models admit simple, fast inference. However, they are not well suited to phenomena such as occlusion, where multiple components of an object may dis...
Sergey Ioffe, David A. Forsyth
SMC
2007
IEEE
143views Control Systems» more  SMC 2007»
14 years 2 months ago
Enabling gestural interaction by means of tracking dynamical systems models and assistive feedback
— The computational understanding of continuous human movement plays a significant role in diverse emergent applications in areas ranging from human computer interaction to phys...
Yon Visell, Jeremy R. Cooperstock
AAAI
2008
13 years 10 months ago
Multimodal People Detection and Tracking in Crowded Scenes
This paper presents a novel people detection and tracking method based on a multi-modal sensor fusion approach that utilizes 2D laser range and camera data. The data points in the...
Luciano Spinello, Rudolph Triebel, Roland Siegwart
ICML
2010
IEEE
13 years 8 months ago
Learning Temporal Causal Graphs for Relational Time-Series Analysis
Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...