We investigate the application of genetic algorithms (GAs) for recognizing real two-dimensional (2-D) or three-dimensional (3-D) objects from 2-D intensity images, assuming that th...
George Bebis, Evangelos A. Yfantis, Sushil J. Loui...
Several real-world applications need to effectively manage and reason about large amounts of data that are inherently uncertain. For instance, pervasive computing applications mus...
Daisy Zhe Wang, Eirinaios Michelakis, Minos N. Gar...
hey generalize these factors to the abstract concepts of ability, integrity, and benevolence. This model does not use probabilistic decision theory. Other SCM trust factors have be...
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
In this paper, we develop multilingual supervised latent Dirichlet allocation (MLSLDA), a probabilistic generative model that allows insights gleaned from one language's data...