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» A Spectral Algorithm for Learning Hidden Markov Models
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CVPR
2010
IEEE
14 years 4 months ago
What's going on? Discovering Spatio-Temporal Dependencies in Dynamic Scenes
We present two novel methods to automatically learn spatio-temporal dependencies of moving agents in complex dynamic scenes. They allow to discover temporal rules, such as the rig...
Daniel Kuettel, Michael Breitenstein, Luc Van Gool...
CORR
2010
Springer
105views Education» more  CORR 2010»
13 years 6 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
ICRA
2006
IEEE
82views Robotics» more  ICRA 2006»
14 years 1 months ago
Behavior Modeling in Man-machine Cooperative System based on Stochastic Switched Dynamics
— This paper presents a new mathematical model for the human behavior called Stochastic Switched Linear Dynamical (SS-LD) model. The SS-LD model can be regarded as a natural exte...
Naoyuki Yamada, Shinkichi Inagaki, Tatsuya Suzuki,...
DAGSTUHL
2007
13 years 9 months ago
Logical Particle Filtering
Abstract. In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical par...
Luke S. Zettlemoyer, Hanna M. Pasula, Leslie Pack ...
ATAL
2007
Springer
14 years 1 months ago
Automatic annotation of team actions in observations of embodied agents
Recognizing and annotating the occurrence of team actions in observations of embodied agents has applications in surveillance and in training of military or sport teams. We descri...
Linus J. Luotsinen, Hans Fernlund, Ladislau Bö...