Long-term predictions of future dangerousness are used throughout the criminal law in investigation, pretrial detention, bail, sentencing, prison administration, parole, and early release decisions. Explicit use of such predictions by courts and legislatures is increasing. Reliance on predictions of dangerousness raises questions about the definition of dangerousness, the ethical limits on the ...

The aim of superstring phenomenology is to develop the tools and methodology needed to confront string theory with experimental data. The first mandatory task is to find string solutions which reproduce the observable data. The subsequent goal is to extract potential signatures beyond the observable data. Recently, by studying exact flat directions of non–Abelian singlet fields, we demonstrated...

CARL G. HEMPEL '-Fb v Ga v Ha'. Kim shows generally that his additional requirement blocks the proofs offered by Eberle, Kaplan, and Montague for the five theorems that "trivialize" the defintions (7.8) and (7.9). However, it would be desirable to ascertain more clearly to what extent the additional requirement is justifiable, not on the ad hoc ground that it blocks those proofs, but in terms o...

Structured prediction tasks pose a fundamental trade off between the need for model complexity to increase predictive power and the limited computational resources for inference in the exponentially-sized output spaces such models require. We formulate and develop structured prediction cascades: a sequence of increasingly complex models that progressively filter the space of possible outputs. W...

We consider algorithms for combining advice from a set of experts. In each trial, the algorithm receives the predictions of the experts and produces its own prediction. A loss function is applied to measure the discrepancy between the predictions and actual observations. The algorithm keeps a weight for each expert. At each trial the weights are first used to help produce the prediction and the...

According to probabilistic theories of higher cognition, beliefs come in degrees. Here, we test this idea by studying how people make predictions from uncertain beliefs. According to the degrees-of-belief theory, people should take account of both highand low-probability beliefs when making predictions that depend on which of those beliefs are true. In contrast, according to the all-or-none the...

The authors report 7 experiments indicating that conditional predictions--the assessed probability that a certain outcome will occur given a certain condition--tend to be markedly inflated. The results suggest that this inflation derives in part from backward activation in which the target outcome highlights aspects of the condition that are consistent with that outcome, thus supporting the pla...

A central problem for real-time scheduling is to acquire tight but conservative upper bounds on task execution times. We present a prototype for an environment where such bounds are interactively presented in terms of source code constructs to the programmer during development. The prototype is based on the language development tool APPLAB and uses an extended attribute grammar formalism, refer...

Research shows that people display a downward shift in their predictions in anticipation of performance and feedback. The authors used a misattribution paradigm to explore whether anxiety serves as a signal for predictions. Participants (N = 108) anticipating results from an important test either immediately or in a few days were or were not encouraged to attribute any arousal they experienced ...