Many program veriication, testing and performance prediction techniques rely on analysis of statically-identiied control-ow paths. However, some such paths may be semantically`dead' because they can never be followed at run time, and should therefore be excluded from analysis. It is shown how the formal semantics of those statements comprising a path provides a sound theoretical foundation for ...

One of the main tasks to analyze and design a mining system is predicting the behavior exhibited by prices in the future. In this paper, the applications of different prediction methods are evaluated in econometrics and financial management fields, such as ARIMA, TGARCH, and stochastic differential equations, for the time-series of monthly copper prices. Moreover, the performance of these metho...

The spectrum of approaches to performance prediction of parallel systems ranges from low-cost, lowprecision compile-time methods to high-cost, highprecision methods with an equal variety of underlying modeling formalisms (e.g., task graphs, queueing networks, simulation languages) which are mutually incompatible. A performance prediction technique is described which uni es a number of existing ...

Todays fixed-cycle traffic signaling is highly suboptimal and aggravates traffic congestion and waste of energy in urban areas. In addition, it offers no quality-of-service guarantee and makes travel time prediction extremely hard. While existing traffic light control research primarily focuses on improving the average wait time of cars, we study in this paper how traffic light scheduling affec...

Recently there has been much interest in modeling the activity of primate midbrain dopamine neurons as signalling reward prediction error. But since the models are based on temporaldi!erence (TD) learning, they assume an exponential decline with time in the value of delayed reinforcers, an assumption long known to con#ict with animal behavior. We show that a variant of TD learning that tracks v...

We consider an adversarial formulation of the problem of predicting a time series with square loss. The aim is to predict an arbitrary sequence of vectors almost as well as the best smooth comparator sequence in retrospect. Our approach allows natural measures of smoothness such as the squared norm of increments. More generally, we consider a linear time series model and penalize the comparator...

We consider a branching process with Poissonian immigration where individuals have inheritable types. At rate θ, new individuals singly enter the total population and start a new population which evolves like a supercritical, homogeneous, binary Crump-Mode-Jagers process: individuals have i.i.d. lifetimes durations (non necessarily exponential) during which they give birth independently at cons...

In this paper we present results we obtained using a compiler to predict performance of scienti c codes. The compiler, Polaris [3], is both the primary tool for estimating the performance of a range of codes, and the bene ciary of the results obtained from predicting the program behavior at compile time. We show that a simple compile-time model, augmented with pro ling data obtained using very ...

A cycle extractor is presented to be used in a speech coder independently from the coding stage. It samples cycle waveforms (CyWs) of the original prediction residual signal at their natural nonuniform rate. It is shown that perfect reconstruction is possible due to the interplay of these properties for two cycle length normalization and denormalization techniques. The coding stage is coupled t...