24 search results - page 3 / 5 » Recommendation as a Stochastic Sequential Decision Problem |
JAIR
2011
14 years 6 months ago
2011
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
116
click to vote
JAIR
2008
14 years 11 months ago
2008
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
101
click to vote
SAC
2005
ACM
15 years 5 months ago
2005
ACM
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
AAMAS
2010
Springer
14 years 11 months ago
2010
Springer
POMDPs and their decentralized multiagent counterparts, DEC-POMDPs, offer a rich framework for sequential decision making under uncertainty. Their computational complexity, howeve...
105
click to vote
CORR
2011
Springer
14 years 6 months ago
2011
Springer
The analysis of online least squares estimation is at the heart of many stochastic sequential decision-making problems. We employ tools from the self-normalized processes to provi...