145 search results - page 16 / 29 » Bayesian Network Learning with Parameter Constraints |
60
Voted
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a nov...
INFOCOM
2008
IEEE
15 years 3 months ago
2008
IEEE
—Knowledge of the network path properties such as latency, hop count, loss and bandwidth is key to the performance of overlay networks, grids and p2p applications. Network operat...
76
Voted
IJON
2008
14 years 9 months ago
2008
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
CVPR
1999
IEEE
15 years 11 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
96
Voted
CORR
2010
Springer
14 years 9 months ago
2010
Springer
We consider the restless multi-armed bandit (RMAB) problem with unknown dynamics. In this problem, at each time, a player chooses K out of N (N > K) arms to play. The state of ...