In the secure communication areas, three-party authenticated key exchange protocol is an important cryptographic technique. In this protocol, two clients will share a human-memorable password with a trusted server, in which two users can generate a secure session key. On the other hand the protocol should resist all types of password guessing attacks. Recently, STPKE’ protocol has been proposed...

In item response theory, the classical estimators of ability are highly sensitive to response disturbances and can return strongly biased estimates of the true underlying ability level. Robust methods were introduced to lessen the impact of such aberrant responses on the estimation process. The computation of asymptotic (i.e., large-sample) standard errors (ASE) for these robust estimators, how...

A standard correction for random guessing on multiple-choice examinations was implemented prospectively in an Oral and Maxillofacial Pathology course for second-year dental students. The correction was a weighted scoring formula for points awarded for correct answers, incorrect answers, and unanswered questions such that the expected gain in the multiple-choice examination score due to random g...

A standard correction for random guessing on multiple-choice examinations was examined retrospectively in an oral and maxillofacial pathology course for second-year dental students. The correction was a weighting formula for points awarded for correct answers, incorrect answers, and unanswered questions such that the expected value of the increase in test score due to guessing was zero. We comp...

In an earlier paper, we studied the problem of guessing a random vector X within distortion D, and characterized the best attainable exponent E(D; ) of the th moment of the number of required guesses G(X) until the guessing error falls below D. In this paper, we extend these results to a multi-stage, hierarchical guessing model, which allows for a faster search of a codeword vector at the encod...

Context: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal foundation to interpret results with a particular focus on continuous prediction systems. Method: A new framework is proposed for evaluating competing predict...

The problem of constructing weak classifiers for boosting algorithms is studied. We present an algorithm that produces a linear classifier that is guaranteed to achieve an error better than random guessing for any distribution on the data. While this weak learner is not useful for learning in general, we show that under reasonable conditions on the distribution it yields an effective weak learn...

If one has a multiclass classification problem and wants to boost a multiclass base classifier AdaBoost.M1 is a well known and widely applicated boosting algorithm. However AdaBoost.M1 does not work, if the base classifier is too weak. We show, that with a modification of only one line of AdaBoost.M1 one can make it usable for weak base classifiers, too. The resulting classifier AdaBoost.M1W is...

We investigate the problem of estimating a random variable Y ∈ Y under a privacy constraint dictated by another correlated random variable X ∈ X , where estimation efficiency and privacy are assessed in terms of two different loss functions. In the discrete case, we use the Hamming loss function and express the corresponding utility-privacy tradeoff in terms of the privacy-constrained guessing ...