Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Relevance feedback (RF) and region-based image retrieval (RBIR) are two widely used methods to enhance the performance of contentbased image retrieval (CBIR) systems. In this paper...
We consider the problem of learning mixtures of distributions via spectral methods and derive a tight characterization of when such methods are useful. Specifically, given a mixt...
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
In this paper, we address the issue of Euclidean path modeling in a single camera for activity monitoring in a multi-camera video surveillance system. The method consists of a pat...