1176 search results - page 30 / 236 » Sparse reward processes |
110
Voted
AIPS
2000
15 years 5 months ago
2000
Goal-directed Markov Decision Process models (GDMDPs) are good models for many decision-theoretic planning tasks. They have been used in conjunction with two different reward stru...
154
Voted
ICA
2010
Springer
15 years 4 months ago
2010
Springer
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
133
Voted
ICN
2005
Springer
15 years 9 months ago
2005
Springer
: Data filtering is an important approach to reduce energy consumption. Following this idea, Interest is used as a constraint to filter uninterested data in sensor networks. Within...
115
Voted
WSC
2008
15 years 6 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
121
Voted
ICIP
2001
IEEE
16 years 5 months ago
2001
IEEE
An elementary proof of a basic uncertainty principle concerning pairs of representations of ?? vectors in different orthonormal bases is provided. The result, slightly stronger th...