908 search results - page 98 / 182 » Stochastic Finite Learning |
126
Voted
EUROCOLT
1995
Springer
15 years 6 months ago
1995
Springer
k. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multi...
134
Voted
ICML
2010
IEEE
15 years 21 days ago
2010
IEEE
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
128
Voted
NIPS
1998
15 years 4 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
128
Voted
NIPS
1996
15 years 4 months ago
1996
In cellular telephone systems, an important problem is to dynamically allocate the communication resource channels so as to maximize service in a stochastic caller environment. Th...
121
Voted
ICML
1998
IEEE
16 years 3 months ago
1998
IEEE
Stochastic topological models, and hidden Markov models in particular, are a useful tool for robotic navigation and planning. In previous work we have shown how weak odometric dat...