multi-input, multi-output feed-back control design for linear systems using the paradigms, theory, and tools of robust con-trol that have arisen during the past two decades. The book is aimed at graduate students and practicing engineers who have a basic knowledge of classical con-trol design

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This paper presents an approach to automatically optimizing the retrieval quality of search engines using clickthrough data. Intuitively, a good information retrieval system should present relevant documents high in the ranking, with less relevant documents following below. While previous

This paper studies a difficult and fundamental problem that arises throughout electrical engineering, applied mathematics, and statistics. Suppose that one forms a short linear combination of elementary signals drawn from a large, fixed collection. Given an observation of the linear combination

for this database is the TIdigits, consisting of connected digits task spoken by American English talkers (downsampled to 8kHz). A selection of 8 different real-world noises have been added to the speech over a range of signal to noise ratios with controlled filtering of the speech and noise. The framework

Abstract. Active learning differs from "learning from examples " in that the learning algorithm assumes at least some control over what part of the input domain it receives information about. In some situations, active learning is provably more powerful than learning from examples

computationally effective reasoning algorithm based on constraint- propagation. This system is notable in offering a delicate balance between expressive power and the efficiency of its deductive engine. A notion of reference intervals is introduced which captures the temporal hierarchy implicit in many domains

For wireless cellular communication systems, one seeks a simple effective means of power control of signals associated with randomly dispersed users that are reusing a single channel in different cells. By effecting the lowest interference environment, in meeting a required minimum signal

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induction, CN2, Laplace, noise 1 Introduction Rule induction from examples has established itself as a basic component of many machine learning systems, and has been the first ML technology to deliver commercially successful applications (eg. the systems GASOIL [Slocombe et al., 1986], BMT [Hayes