For nearly a century the two most powerful nations on earth - Victorian Britain and Tsarist Russia - fought a secret war in the lonely passes and deserts of Central Asia. Those engaged in this shadowy struggle called it 'The Great Game', a phrase immortalized in Kipling's Kim.
When play first began the two rival empires lay nearly 2,000 miles apart. By the end, some Russian outposts were within 20 miles of India.
This classic book tells the story of the Great Game through the exploits of the young officers, both British and Russian, who risked their lives playing it. Disguised as holy men or native horse-traders, they mapped secret passes, gathered intelligence and sought the allegiance of powerful khans. Some never returned. The violent repercussions of the Great Game are still convulsing Central Asia today.

This book is an English translation of the famous "Green Book" by Lafontaine and Pansu (1979). It has been enriched and expanded with new material to reflect recent progress. Additionally, four appendices, by Gromov on Levy's inequality, by Pansu on "quasiconvex" domains, by Katz on systoles of Riemannian manifolds, and by Semmes overviewing analysis on metric spaces with measures, as well as an extensive bibliography and index round out this unique and beautiful book.

Fitztroy Maclean was one of the real-life inspirations for super-spy James Bond. After adventures in Soviet Russia before the war, Maclean fought with the SAS in North Africa in 1942. There he specialised in hair-raising commando raids behind enemy lines, including the daring and outrageous kidnapping of the German Consul in Axis-controlled Iraq. Maclean's extraordinary adventures in the Western Desert and later fighting alongside Tito's partisans in Yugoslavia are blistering reading and show what it took to be a British hero who broke the mould...

Kim Philby was the greatest spy in history, a brilliant and charming man who rose to head Britain’s counterintelligence against the Soviet Union during the height of the Cold War—while he was secretly working for the enemy. And nobody thought he knew Philby like Nicholas Elliott, Philby’s best friend and fellow officer in MI6. The two men had gone to the same schools, belonged to the same exclusive clubs, grown close through the crucible of wartime intelligence work and long nights of drink and revelry. It was madness for one to think the other might be a communist spy, bent on subverting Western values and the power of the free world.
But Philby was secretly betraying his friend. Every word Elliott breathed to Philby was transmitted back to Moscow—and not just Elliott’s words, for in America, Philby had made another powerful friend: James Jesus Angleton, the crafty, paranoid head of CIA counterintelligence. Angleton's and Elliott’s unwitting disclosures helped Philby sink almost every important Anglo-American spy operation for twenty years, leading countless operatives to their doom. Even as the web of suspicion closed around him, and Philby was driven to greater lies to protect his cover, his two friends never abandoned him—until it was too late. The stunning truth of his betrayal would have devastating consequences on the two men who thought they knew him best, and on the intelligence services he left crippled in his wake.
Told with heart-pounding suspense and keen psychological insight, and based on personal papers and never-before-seen British intelligence files, A Spy Among Friends is Ben Macintyre’s best book yet, a high-water mark in Cold War history telling.

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

The Foundation has managed to preserve humanculture and shorten the period of chaotic barbarism after the Galactic Empire began to decay. But the Foundation still faces great challenges in its struggle to survive.

A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.