125 search results - page 19 / 25 » The Stochastic Machine Replenishment Problem |
ICML
2009
IEEE
14 years 10 months ago
2009
IEEE
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
ICML
2009
IEEE
14 years 10 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
ICML
2006
IEEE
14 years 10 months ago
2006
IEEE
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
ICML
2004
IEEE
14 years 10 months ago
2004
IEEE
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
MLDM
2009
Springer
14 years 4 months ago
2009
Springer
Abstract. Regression models are often required for controlling production processes by predicting parameter values. However, the implicit assumption of standard regression techniqu...