Abstract. In recent work binary decision diagrams (BDDs) were introduced as a technique for postoptimality analysis for integer programming. In this paper we show that much smaller...
With resource-efficient summarization and accurate reconstruction of the historic traffic sensor data, one can effectively manage and optimize transportation systems (e.g., road n...
Bei Pan, Ugur Demiryurek, Farnoush Banaei Kashani,...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
One of the main research concern in neural networks is to find the appropriate network size in order to minimize the trade-off between overfitting and poor approximation. In this ...
In a variety of applications (including automatic target recognition) image classification algorithms operate on compressed image data. This paper explores the design of optimal t...