We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of in...
For large investment projects sensitivity analysis is an important tool to determine which factors need further analysis and/or can jeopardize the future of a project. In practice...
We present N-gram GP, an estimation of distribution algorithm for the evolution of linear computer programs. The algorithm learns and samples the joint probability distribution of...
Abstract. This paper proposes an algorithm for combinatorial optimizations that uses reinforcement learning and estimation of joint probability distribution of promising solutions ...
In recent years, statistical language models are being proposed as alternative to the vector space model. Viewing documents as language samples introduces the issue of defining a...
In this paper, we propose a method for jointly computing optical flow and segmenting video while accounting for mixed pixels (matting). Our method is based on statistical modelin...
C. Lawrence Zitnick, Nebojsa Jojic, Sing Bing Kang
Multiagent Bayesian networks (MABNs) are a powerful new framework for uncertainty management in a distributed environment. In a MABN, a collective joint probability distribution i...
With device size shrinking and fast rising frequency ranges, effect of cosmic radiations and alpha particles known as Single-Event-Upset (SEU), Single-Eventtransients (SET), is a ...
Mohammad Gh. Mohammad, Laila Terkawi, Muna Albasma...
We extend a recently developed method [1] for learning the semantics of image databases using text and pictures. We incorporate statistical natural language processing in order to...