Accurately characterizing the resource usage of an application at various levels in the memory hierarchy has been a long-standing research problem. Existing characterization studi...
Sequence data are abundant in application areas such as computational biology, environmental sciences, and telecommunications. Many real-life sequences have a strong segmental str...
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
We present a model of a `gas of circles', the ensemble of regions in the image domain consisting of an unknown number of circles with approximately fixed radius and short ran...
Peter Horvath, Ian Jermyn, Zoltan Kato, and Josian...
The paper provides a unifying perspective of tree-decomposition algorithms appearing in various automated reasoning areas such as join-tree clustering for constraint-satisfaction ...
Kalev Kask, Rina Dechter, Javier Larrosa, Avi Dech...