Evaluation, prioritization and selection of candidate requirements are of tremendous importance and impact for subsequent software development. Effort, time as well as quality constraints have to be taken into account. Typically, different stakeholders have conflicting priorities and the requirements of all these stakeholders have to be balanced in an appropriate way to ensure maximum value of ...

Action selection requires a policy that maps states of the world to distribution over actions. The amount memory needed specify (the complexity) increases with state-dependence policy. If there is capacity limit for complexity, then will also be trade-off between reward and since some need sacrificed in order satisfy constraint. This paper empirically characterizes complexity both schizophrenia...

Evolutionary singularities are central to the adaptive dynamics of evolving traits. The evolutionary singularities are strongly affected by the shape of any trade-off functions a model assumes, yet the trade-off functions are often chosen in an ad hoc manner, which may unjustifiably constrain the evolutionary dynamics exhibited by the model. To avoid this problem, critical function analysis has...

Following the famous Netflix Prize competition, accuracy metrics (such as RMSE) became a de facto standard in the community to evaluate and compare performance of recommendation algorithms. However, it has been shown, that accuracy is not the best way to quantify the quality of recommendations, especially in the context of predicting online performance from offline evaluations [1]. Thus, it mak...

We present size-space trade-offs for the polynomial calculus (PC) and polynomial calculus resolution (PCR) proof systems. These are the first true size-space trade-offs in any algebraic proof system, showing that size and space cannot be simultaneously optimized in these models. We achieve this by extending essentially all known size-space trade-offs for resolution to PC and PCR. As such, our r...

Qualitative probabilistic networks have been introduced as qualitative abstractions of Bayesian belief networks. One of the major drawbacks of these qualitative networks is their coarse level of detail, which may lead to unresolved trade-offs during inference. We present an enhanced formalism for qualitative networks with a finer level of detail. An enhanced qualitative probabilistic network di...

Both cloud and GRID are computing paradigms that manage large distributed resources, and currently there is a lot of interest in their integration. An integrated architecture cloud-GRID requires fine-grained access control and identity federation among untrusted distributed domains in the cloud. This paper deals with the trade-off between security and performance in such architectures, comparin...