Multiobjective optimization deals with problems involving multiple measures of performance that should be optimized simultaneously. In this paper we extend bucket elimination (BE),...
Dynamic Programming solves combinatorial optimization problems by recursive decomposition and tabulation of intermediate results. The first step in the design of a dynamic program...
In this paper, we address the rate control problem for layered multicast traffic, with the objective of solving a generalized throughput/fairness objective. Our approach is based o...
The paper presents a new sampling methodology for Bayesian networks that samples only a subset of variables and applies exact inference to the rest. Cutset sampling is a network s...
Research on bias in machine learning algorithms has generally been concerned with the impact of bias on predictive accuracy. We believe that there are other factors that should al...