In this paper we try to organize machine teaching as a coherent set of ideas. Each idea is
presented as varying along a dimension. The collection of dimensions then form the …

Machine learning is one of the fastest growing areas of computer science, with far-reaching
applications. The aim of this textbook is to introduce machine learning, and the algorithmic …

This is the first comprehensive introduction to Support Vector Machines (SVMs), a new
generation learning system based on recent advances in statistical learning theory. SVMs …

Adding examples of the majority class to the training set can have a detrimental e ect on the
learner's behavior: noisy or otherwise unreliable examples from the majority class can …

The exponential growth of computer applications in the last three decades of the 20th
century has resulted in an explosive growth in the amounts of data moved between …

Vladimir Vovk Alexander Gammerman Glenn Shafer Second Edition Page 1 Vladimir Vovk
Alexander Gammerman Glenn Shafer Algorithmic Learning in a Random World Second …

We present an algorithm for improving the accuracy of algorithms for learning binary
concepts. The improvement is achieved by combining a large number of hypotheses, each …

During a project examining the use of machine learning techniques for oil spill detection, we
encountered several essential questions that we believe deserve the attention of the …

This paper proposes a new probabilistic solution framework for robust control analysis and
synthesis problems that can be expressed in the form of minimization of a linear objective …

The study of NIP theories has received much attention from model theorists in the last
decade, fuelled by applications to o-minimal structures and valued fields. This book, the first …