High Dimensional Probability

¡
¡ Progress in Probability āĻŦāχ 43 ¡ Birkhäuser
āχ-āĻŦ⧁āĻ•
335
āĻĒ⧃āĻˇā§āĻ āĻž
āϰ⧇āϟāĻŋāĻ‚ āĻ“ āϰāĻŋāĻ­āĻŋāω āϝāĻžāϚāĻžāχ āĻ•āϰāĻž āĻšā§ŸāύāĻŋ  āφāϰāĻ“ āϜāĻžāύ⧁āύ

āĻāχ āχ-āĻŦ⧁āϕ⧇āϰ āĻŦāĻŋāĻˇā§Ÿā§‡

What is high dimensional probability? Under this broad name we collect topics with a common philosophy, where the idea of high dimension plays a key role, either in the problem or in the methods by which it is approached. Let us give a specific example that can be immediately understood, that of Gaussian processes. Roughly speaking, before 1970, the Gaussian processes that were studied were indexed by a subset of Euclidean space, mostly with dimension at most three. Assuming some regularity on the covariance, one tried to take advantage of the structure of the index set. Around 1970 it was understood, in particular by Dudley, Feldman, Gross, and Segal that a more abstract and intrinsic point of view was much more fruitful. The index set was no longer considered as a subset of Euclidean space, but simply as a metric space with the metric canonically induced by the process. This shift in perspective subsequently lead to a considerable clarification of many aspects of Gaussian process theory, and also to its applications in other settings.

āχ-āĻŦ⧁āϕ⧇ āϰ⧇āϟāĻŋāĻ‚ āĻĻāĻŋāύ

āφāĻĒāύāĻžāϰ āĻŽāϤāĻžāĻŽāϤ āϜāĻžāύāĻžāύāĨ¤

āĻĒāĻ āύ āϤāĻĨā§āϝ

āĻ¸ā§āĻŽāĻžāĻ°ā§āϟāĻĢā§‹āύ āĻāĻŦāĻ‚ āĻŸā§āϝāĻžāĻŦāϞ⧇āϟ
Android āĻāĻŦāĻ‚ iPad/iPhone āĻāϰ āϜāĻ¨ā§āϝ Google Play āĻŦāχ āĻ…ā§āϝāĻžāĻĒ āχāύāĻ¸ā§āϟāϞ āĻ•āϰ⧁āύāĨ¤ āĻāϟāĻŋ āφāĻĒāύāĻžāϰ āĻ…ā§āϝāĻžāĻ•āĻžāωāĻ¨ā§āĻŸā§‡āϰ āϏāĻžāĻĨ⧇ āĻ…āĻŸā§‹āĻŽā§‡āϟāĻŋāĻ• āϏāĻŋāĻ™ā§āĻ• āĻšā§Ÿ āĻ“ āφāĻĒāύāĻŋ āĻ…āύāϞāĻžāχāύ āĻŦāĻž āĻ…āĻĢāϞāĻžāχāύ āϝāĻžāχ āĻĨāĻžāϕ⧁āύ āύāĻž āϕ⧇āύ āφāĻĒāύāĻžāϕ⧇ āĻĒ⧜āϤ⧇ āĻĻā§‡ā§ŸāĨ¤
āĻ˛ā§āϝāĻžāĻĒāϟāĻĒ āĻ“ āĻ•āĻŽā§āĻĒāĻŋāωāϟāĻžāϰ
Google Play āĻĨ⧇āϕ⧇ āϕ⧇āύāĻž āĻ…āĻĄāĻŋāĻ“āĻŦ⧁āĻ• āφāĻĒāύāĻŋ āĻ•āĻŽā§āĻĒāĻŋāωāϟāĻžāϰ⧇āϰ āĻ“ā§Ÿā§‡āĻŦ āĻŦā§āϰāĻžāωāϜāĻžāϰ⧇ āĻļ⧁āύāϤ⧇ āĻĒāĻžāϰ⧇āύāĨ¤
eReader āĻāĻŦāĻ‚ āĻ…āĻ¨ā§āϝāĻžāĻ¨ā§āϝ āĻĄāĻŋāĻ­āĻžāχāϏ
Kobo eReaders-āĻāϰ āĻŽāϤ⧋ e-ink āĻĄāĻŋāĻ­āĻžāχāϏ⧇ āĻĒāĻĄāĻŧāϤ⧇, āφāĻĒāύāĻžāϕ⧇ āĻāĻ•āϟāĻŋ āĻĢāĻžāχāϞ āĻĄāĻžāωāύāϞ⧋āĻĄ āĻ“ āφāĻĒāύāĻžāϰ āĻĄāĻŋāĻ­āĻžāχāϏ⧇ āĻŸā§āϰāĻžāĻ¨ā§āϏāĻĢāĻžāϰ āĻ•āϰāϤ⧇ āĻšāĻŦ⧇āĨ¤ āĻŦā§āϝāĻŦāĻšāĻžāϰāĻ•āĻžāϰ⧀āϰ āωāĻĻā§āĻĻ⧇āĻļā§āϝ⧇ āϤ⧈āϰāĻŋ āϏāĻšāĻžā§ŸāϤāĻž āϕ⧇āĻ¨ā§āĻĻā§āϰāϤ⧇ āĻĻ⧇āĻ“ā§ŸāĻž āύāĻŋāĻ°ā§āĻĻ⧇āĻļāĻžāĻŦāϞ⧀ āĻ…āύ⧁āϏāϰāĻŖ āĻ•āϰ⧇ āϝ⧇āϏāĻŦ eReader-āĻ āĻĢāĻžāχāϞ āĻĒāĻĄāĻŧāĻž āϝāĻžāĻŦ⧇ āϏ⧇āĻ–āĻžāύ⧇ āĻŸā§āϰāĻžāĻ¨ā§āϏāĻĢāĻžāϰ āĻ•āϰ⧁āύāĨ¤

āϏāĻŋāϰāĻŋāϜ āĻĒāĻĄāĻŧāĻž āϚāĻžāϞāĻŋā§Ÿā§‡ āϝāĻžāύ

Ernst Eberlein āĻāϰ āĻĨ⧇āϕ⧇ āφāϰ⧋

āĻāĻ•āχ āϧāϰāύ⧇āϰ āχ-āĻŦ⧁āĻ•