This paper presents a performance analysis of marketbased batch schedulers for clusters of workstations. In contrast to previous work, we use user-centric performance metrics as t...
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
We define the crouching Dirichlet, hidden Markov model (CDHMM), an HMM for partof-speech tagging which draws state prior distributions for each local document context. This simple...
This paper describes a noise-aware dominance operator for evolutionary algorithms to solve the multiobjective optimization problems (MOPs) that contain noise in their objective fu...
We consider the problem of aggregation for uncertain and imprecise data. For such data, we define aggregation operators and use them to provide information on properties and patte...