In this paper incremental discovery of sequential patterns from a large sequence database is studied A sequential pattern has the form where and are subsequences in the database which says that events will be followed by events with some minimum support and con dence We consider the scenario that sequential patterns have previously been discovered and materialized and an update is subsequently ...

Standard election models robustly predict that candidates should adopt moderate policies, especially if they value winning o¢ ce, and that this is good for voter welfare. Empirical polarization is therefore both inexplicable and troubling. This paper shows that if voter di¤erences re‡ect beliefs about an underlying truth variable, rather than idiosyncratic preferences, then polarization is the ...

Often when comparing the survival rates of individuals given either of two treatments the analysis stops with a test of the hypothesis of no treatment di erence and perhaps a plot of the two survival functions. The hypothesis test is usually a comparison of the two survival curves over the entire observational period. An alternative approach to this problem is to provide an investigator with a ...

The literature nds that investors increase portfolio turnover following high returns, explaining it by either overcon dence or skilled trading. This paper develops a theoretical model and shows empirically that team-managed funds trade less after good performance than single-managed funds. The magnitude of this di erential increases with team size. Moreover, the change from singleto team-manage...

�e �rst review existing sequential methods for estimating a binomial proportion. A�erward, we propose a new family of group sequential sampling schemes for estimating a binomial proportion with prescribed margin of error and con�dence level. In particular, we establish the uniform controllability of coverage probability and the asymptotic optimality for such a family of sampling schemes. Our th...

We give a method for determining a set of images which are consistent with measured projections data and error bounds on the projections noise The error bounds can account for both statistical noise uncertainty and model uncertainty e g due to a mismodeled or un calibrated system matrix If one knows the statistical distribution of the projections errors then one can se lect the error bounds to ...

This paper describes a robust system for information extraction (IE) from spoken language data. The system extends previous hidden Markov model (HMM) work in IE, using a state topology designed for explicit modeling of variablelength phrases and class-based statistical language model smoothing to produce state-of-the-art performance for a wide range of speech error rates. Experiments on broadca...

We discuss the nature of cognitive representations and present a scheme for the encoding of information which accounts for both categorical and graded aspects of cognitive events. Accordingly, object categories are mapped onto the identity of cell populations via the process of categorical perception, while graded aspects such as vividness and con dence level are mapped onto the rate and degree...

Predictions with Con dence Intervals (Local Error Bars) Andreas S. Weigend Department of Computer Science and Institute of Cognitive Science University of Colorado Boulder, CO 80309-0430 [email protected] David A. Nix Department of Computer Science and Institute of Cognitive Science University of Colorado Boulder, CO 80309-0430 [email protected] Abstract|We present a new method for obt...

Often when comparing the survival rates of individuals given either of two treatments the analysis stops with a test of the hypothesis of no treatment diierence and perhaps a plot of the two survival functions. The hypothesis test is usually a comparison of the two survival curves over the entire observational period. An alternative approach to this problem is to provide an investigator with a ...