Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
In this paper, we discuss challenges and provide solutions for capturing and maintaining accurate models of user profiles using semantic web technologies, by aggregating and shari...
This paper provides a new framework for the derivation and estimation of consumption and the equity premium functions. The novelty in our approach is that it does not require the ...
We present a framework for evaluating and generating access control policies. The framework contains a modelling formalism called RW, which is supported by a model checking tool. ...
Abstract. This tutorial explores the design space of heterogeneous synchronization, which is concerned with establishing consistency among artifacts that conform to different sche...