Preface to this special issue

Abstract

This issue of JMLR is devoted to the memory of Alexey Chervonenkis. Over the period of a dozen years between 1962 and 1973 he and Vladimir Vapnik created a new discipline of statistical learning theory—the foundation on which all our modern understanding of pattern recognition is based. Alexey was 28 years old when they made their most famous and original discovery, the uniform law of large numbers. In that short period Vapnik and Chervonenkis also introduced the main concepts of statistical learning theory, such as VCdimension, capacity control, and the Structural Risk Minimization principle, and designed two powerful pattern recognition methods, Generalised Portrait and Optimal Separating Hyperplane, later transformed by Vladimir Vapnik into Support Vector Machine—arguably one of the best tools for pattern recognition and regression estimation. Thereafter Alexey continued to publish original and important contributions to learning theory. He was also active in research in several applied fields, including geology, bioinformatics, medicine, and advertising. Alexey tragically died in September 2014 after getting lost during a hike in the Elk Island park on the outskirts of Moscow. Vladimir Vapnik suggested to prepare an issue of JMLR to be published at the first anniversary of the death of his long-term collaborator and close friend. Vladimir and the editors contacted a few dozen leading researchers in the fields of machine learning related to Alexey’s research interests and had many enthusiastic replies. In the end eleven papers were accepted. This issue also contains a first attempt at a complete bibliography of Alexey Chervonenkis’s publications. Simultaneously with this special issue will appear Alexey’s Festschrift (Vovk et al., 2015), to which the reader is referred for information about Alexey’s research, life, and death. The Festschrift is based in part on a symposium held in Pathos, Cyprus, in 2013 to celebrate Alexey’s 75th anniversary. Apart from research contributions, it contains Alexey’s reminiscences about his early work on statistical learning with Vladimir Vapnik, a reprint of their seminal 1971 paper, a historical chapter by R. M. Dudley, reminiscences of Alexey’s and Vladimir’s close colleague Vasily Novoseltsev, and three reviews of various measures of complexity used in machine learning (“Measures of Complexity” is both the name of the symposium and the title of the book). Among Alexey’s contributions to machine learning (mostly joint with Vladimir Vapnik) discussed in the book are: