be expressed as a linear-threshold algorithm. A primary advantage of this algorithm is that the number of mistakes grows only logarithmically with the number of irrelevant attributes in the examples. At the same time, the algorithm is computationally efficient in both time and space. 1.

develop a new cryptosystem for fine-grained sharing of encrypted data that we call Key-Policy Attribute-Based Encryption (KP-ABE). In our cryptosystem, ciphertexts are labeled with sets of attributes and private keys are associated with access structures that control which ciphertexts a user is able

descriptive theories have been developed over the last forty years, intended to describe how decisions are made. This paper presents a framework that classifies descriptive theories using a theme of comparison; comparisons involving attributes, alternatives and situations. The paper also reports on research

In an earlier paper, we introduced a new “boosting” algorithm called AdaBoost which, theoretically, can be used to significantly reduce the error of any learning algorithm that consistently generates classifiers whose performance is a little better than random guessing. We also introduced

This paper provides a simple example of an economy in which equi-librium prices and quantities exhibit what may be the central feature of the modern business cycle: a systematic relation between the rate of change in nominal prices and the level of real output. The relationship,

“Having looked at monetary policy from both sides now, I can testify that central banking in practice is as much art as science. Nonetheless, while practicing this dark art, I have always found the science quEite useful.” 2 Alan S. Blinder

that it is difficult to implement, difficult to tune, and only reliable for systems which are almost linear on the time scale of the update intervals. In this paper a new linear estimator is developed and demonstrated. Using the principle that a set of discretely sampled points can be used to parameterise mean

. In the context of machine learning from examples this paper deals with the problem of estimating the quality of attributes with and without dependencies among them. Kira and Rendell (1992a,b) developed an algorithm called RELIEF, which was shown to be very efficient in estimating attributes

The increasing amount of genomic and molecular information is the basis for understanding higherorder biological systems, such as the cell and the 15 organism, and their interactions with the environment, as well as for medical, industrial and other practical applications. The KEGG resource

It has long been recognized that personality test scores are influenced by non-test-relevant response determinants. Wiggins and Rumrill (1959) distinguish three approaches to this problem. Briefly, interest in the problem of response distortion has been concerned with attempts at statistical correction for "faking good " or "faking bad " (Meehl & Hathaway, 1946), the analysis of response sets (Cron-bach, 1946,1950), and ratings of the social de-sirability of personality test items (Edwards, 19 5 7). A further distinction can be made, how-ever, which results in a somewhat different division of approaches to the question of re-sponse distortion. Common to both the Meehl