1218 search results - page 151 / 244 » Scaling up a |
ICML
2009
IEEE
14 years 11 months ago
2009
IEEE
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
KDD
2003
ACM
14 years 10 months ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
INFOCOM
2009
IEEE
14 years 5 months ago
2009
IEEE
—This paper considers the design of opportunistic packet schedulers for users sharing a time-varying wireless channel from the performance and the robustness points of view. Firs...
ATAL
2009
Springer
14 years 4 months ago
2009
Springer
Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...
ATAL
2007
Springer
14 years 4 months ago
2007
Springer
Decentralized Markov Decision Processes (DEC-MDPs) are a popular model of agent-coordination problems in domains with uncertainty and time constraints but very difficult to solve...