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» Aggregation-based model reduction of a Hidden Markov Model
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ALDT
2009
Springer
142views Algorithms» more  ALDT 2009»
14 years 1 months ago
Finding Best k Policies
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Peng Dai, Judy Goldsmith
ICASSP
2010
IEEE
13 years 7 months ago
Towards jointly optimal spatial prediction and adaptive transform in video/image coding
This paper proposes a new approach to combined spatial (Intra) prediction and adaptive transform coding in block-based video and image compression. Context-adaptive spatial predic...
Jingning Han, Ankur Saxena, Kenneth Rose
JAIR
2006
101views more  JAIR 2006»
13 years 6 months ago
Resource Allocation Among Agents with MDP-Induced Preferences
Allocating scarce resources among agents to maximize global utility is, in general, computationally challenging. We focus on problems where resources enable agents to execute acti...
Dmitri A. Dolgov, Edmund H. Durfee
CVPR
2004
IEEE
14 years 8 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
SIGMOD
2007
ACM
192views Database» more  SIGMOD 2007»
14 years 6 months ago
Benchmarking declarative approximate selection predicates
Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize...
Amit Chandel, Oktie Hassanzadeh, Nick Koudas, Moha...