1921 search results - page 259 / 385 » Learning from sensor network data |
152
click to vote
PERVASIVE
2009
Springer
16 years 28 days ago
2009
Springer
This paper presents novel methodologies for the analysis of continuous cellular tower data from 215 randomly sampled subjects in a major urban city. We demonstrate the potential of...
159
click to vote
ICDM
2009
IEEE
16 years 24 days ago
2009
IEEE
—Applying the concept of organizational structure to social network analysis may well represent the power of members and the scope of their power in a social network. In this pap...
151
click to vote
KDD
2003
ACM
16 years 6 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...
184
click to vote
ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
224
Voted
ESANN
2008
15 years 7 months ago
2008
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...