This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
Transcriptional regulation is mediated by the coordinated binding of transcription factors to the upstream regions of genes. In higher eukaryotes, the binding sites of cooperating...
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
In this paper, we propose a new probabilistic generative model, called Topic-Perspective Model, for simulating the generation process of social annotations. Different from other g...
Caimei Lu, Xiaohua Hu, Xin Chen, Jung-ran Park, Ti...