We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed...
Abstract--This work studies the near-optimality versus the complexity of distributed configuration management for wireless networks. We first develop a global probabilistic graphic...
Our participation in TREC 2004 aims to extend and improve the use of the DFR (Divergence From Randomness) models with Query Expansion (QE) for the robust track. We experiment with...
In order to make personalized recommendations, many collaborative music recommender systems (CMRS) focused on capturing precise similarities among users or items based on user hist...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...