A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koll...
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
This paper presents an object categorization method. Our approach involves the following aspects of cognitive vision : machine learning and knowledge representation. A major eleme...
This paper describes a dynamic service reconfiguration model where the proxy is composed of a chain of service objects called mobilets (pronounced as mo-be-lets), which can be dep...
Siu Nam Chuang, Alvin T. S. Chan, Jiannong Cao, Ro...
An ever-increasing amount of data and semantic knowledge in the domain of life sciences is bringing about new data management challenges. In this paper we focus on adding the seman...