Shahar Mendelson – författare

Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11–22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at http://mlg. anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will ?nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop.

Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11–22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at http://mlg. anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will ?nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop.

This collection of original papers related to the Israeli GAFA seminar (on Geometric Aspects of Functional Analysis) from the years 2006 to 2011 continues the long tradition of the previous volumes, which reflect the general trends of Asymptotic Geometric Analysis, understood in a broad sense, and are a source of inspiration for new research. Most of the papers deal with various aspects of the theory, including classical topics in the geometry of convex bodies, inequalities involving volumes of such bodies or more generally, logarithmically-concave measures, valuation theory, probabilistic and isoperimetric problems in the combinatorial setting, volume distribution on high-dimensional spaces and characterization of classical constructions in Geometry and Analysis (like the Legendre and Fourier transforms, derivation and others). All the papers here are original research papers.

This collection of original papers related to the Israeli GAFA seminar (on Geometric Aspects of Functional Analysis) from the years 2006 to 2011 continues the long tradition of the previous volumes, which reflect the general trends of Asymptotic Geometric Analysis, understood in a broad sense, and are a source of inspiration for new research. Most of the papers deal with various aspects of the theory, including classical topics in the geometry of convex bodies, inequalities involving volumes of such bodies or more generally, logarithmically-concave measures, valuation theory, probabilistic and isoperimetric problems in the combinatorial setting, volume distribution on high-dimensional spaces and characterization of classical constructions in Geometry and Analysis (like the Legendre and Fourier transforms, derivation and others). All the papers here are original research papers.