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» Learning multi-agent state space representations
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ICASSP
2011
IEEE
12 years 11 months ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur
CVPR
2009
IEEE
15 years 2 months ago
Efficient Representation of Local Geometry for Large Scale Object Retrieval
State of the art methods for image and object re- trieval exploit both appearance (via visual words) and local geometry (spatial extent, relative pose). In large scale problems,...
Michal Perdoch (Czech Technical University), Ondre...
ACII
2005
Springer
13 years 9 months ago
Simulated Annealing Based Hand Tracking in a Discrete Space
Hand tracking is a challenging problem due to the complexity of searching in a 20+ degrees of freedom (DOF) space for an optimal estimation of hand configuration. This paper repres...
Wei Liang, Yunde Jia, Yang Liu, Cheng Ge
VR
2010
IEEE
188views Virtual Reality» more  VR 2010»
13 years 5 months ago
Illuminating the past: state of the art
Virtual reconstruction and representation of historical environments and objects have been of research interest for nearly two decades. Physically-based and historically accurate ...
Jassim Happa, Mark Mudge, Kurt Debattista, Alessan...
AAAI
2006
13 years 9 months ago
Learning Partially Observable Action Models: Efficient Algorithms
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...
Dafna Shahaf, Allen Chang, Eyal Amir