Titlebook: Algorithmic Learning Theory; 12th International C Naoki Abe,Roni Khardon,Thomas Zeugmann Conference proceedings 2001 Springer-Verlag Berlin

LIMN

Das Konto als Basis der Kunde-Bank-Beziehungies. We then sketch general results on the number of queries needed to learn a class of concepts, focusing on the various notions of combinatorial dimension that have been employed, including the teaching dimension, the exclusion dimension, the extended teaching dimension, the fingerprint dimension,

Serenity

Geld- und Kapitalanlagem?glichkeiten. We discuss several kinds of meaning that representations might have, and focus on a functional notion of meaning as appropriate for programs to learn. Specifically, a representation is meaningful if it incorporates an indicator of external conditions and if the indicator relation informs action. W

本能

insurrection

Derivative Finanzdienstleistungenearchers believe in the importance of giving users an overview and insight into the data distributions, while data mining researchers believe that statistical algorithms and machine learning can be relied on to find the interesting patterns. This paper discusses two issues that influence design of d

憤世嫉俗者

虛弱的神經(jīng)

Das Auslandsdienstleistungsgesch?ftof Mansour and McAllester constructs a multiway branching decision tree using a set of multi-class hypotheses. Mansour and McAllester proved that it works under certain conditions. We give a much simpler analysis of the algorithm and simplify the conditions. From this simplification, we can provide

Soliloquy

avenge

Karl Fr. Hagenmüller,Gerhard Diepen more sophisticated algorithm for classification in discrete attribute spaces. Classification in discrete attribute spaces is reduced to the problem of learning Boolean functions from examples of its input/output behavior. Since any Boolean function can be written in Disjunctive Normal Form (DNF), i

Adrenal-Glands

Karl Fr. Hagenmüller,Gerhard Diepenues for training support vector machines (more precisely, primal-form maximal-margin classifiers) that solve two-group classification problems by using hyperplane classifiers. Through this research, we are aiming (I) to design efficient and theoretically guaranteed support vector machine training al

流眼淚

Karl Fr. Hagenmüller,Gerhard Diepenitive learning situations, where “natural” constraints are imposed on the outcomes of classifiers so that a valid sentence, image or any other domain representation is produced. We formalize these learning situations, after a model suggested in [.] and study generalization abilities of learning algo