This paper surveys quantum learning theory: the theoretical aspects of machine learning
using quantum computers. We describe the main results known for three models of learning …

Abstract Language is our legacy. It is the main evolutionary contribution of humans, and
perhaps the most interesting trait that has emerged in the past 500 million years …

At a time of unprecedented expansion in the life sciences, evolution is the one theory that
transcends all of biology. Any observation of a living system must ultimately be interpreted in …

Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani
introduce a number of central topics in computational learning theory for researchers and …

In this paper, we prove the intractability of learning several classes of Boolean functions in
the distribution-free model (also called the Probably Approximately Correct or PAC model) of …

The problem of inducing, learning or inferring grammars has been studied for decades, but
only in recent years has grammatical inference emerged as an independent field with …

We describe efficient constructions for various cryptographic primitives in private-key as well
as public-key cryptography. Our main results are two new constructions of pseudo-random …

Modern cryptography has had considerable impact on the development of computational
learning theory. Virtually every intractability result in Valiant's model [13](which is …

Cryptology is the practice of hiding digital information by means of various obfuscatory and
steganographic techniques. The application of said techniques facilitates message …

This handbook provides an up-to-date compendium of fundamental computer science
topics, techniques, and applications. Along with updating and revising many of the existing …