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...
—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...
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
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...
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...