154 search results - page 10 / 31 » Hierarchical Non-Emitting Markov Models |
ICML
2008
IEEE
14 years 10 months ago
2008
IEEE
The dynamic hierarchical Dirichlet process (dHDP) is developed to model the timeevolving statistical properties of sequential data sets. The data collected at any time point are r...
ICML
2001
IEEE
14 years 10 months ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
UAI
1998
13 years 11 months ago
1998
tigate the use of temporally abstract actions, or macro-actions, in the solution of Markov decision processes. Unlike current models that combine both primitive actions and macro-...
KI
2007
Springer
14 years 3 months ago
2007
Springer
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person’s activities and signiď¬...
ICIP
2010
IEEE
13 years 7 months ago
2010
IEEE
Pitching is the starting point of an event in baseball games. Hence, locating pitching shots is a critical step in content analysis of a baseball game video. However, pitching fra...